Individualized cancer therapy

ABSTRACT

In certain preferred embodiments, the invention provides methods for treating cancer, which comprise (a) obtaining a specimen of cancer tissue from a patient; (b) obtaining a specimen of normal tissue in the proximity of the cancer tissue from such patient; (c) extracting total protein and RNA from the cancer tissue and normal tissue; (d) obtaining a protein expression profile of the cancer tissue and normal tissue using 2D DIGE and mass spectrometry; (e) identifying proteins that are expressed in such cancer tissue at significantly different levels than in the normal tissue; (f) obtaining a gene expression profile of the cancer tissue and normal tissue using microarray technology and comparing the results thereof to the protein expression profile; (g) prioritizing over-expressed proteins by assessing the connectivity thereof to other cancer-related or stimulatory proteins; (h) designing an appropriate RNA interference expression cassette to, directly or indirectly, modulate the expression of genes encoding such prioritized proteins; (i) incorporating said cassette into an appropriate delivery vehicle; and (j) providing the patient with an effective amount of the delivery vehicle to directly or indirectly, modify the expression (i.e., production) of such proteins.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to, and incorporates by reference, U.S.provisional patent application Ser. No. 60/772,015, filed Feb. 10, 2006,and U.S. provisional patent application Ser. No. 60/738,160, filed Nov.18, 2005, which is a continuation of U.S. application Ser. No.11/601,431, filed Nov. 17, 2006, which is a continuation of U.S. Ser.No. 14/071,490, filed Nov. 4, 2013.

FIELD OF THE INVENTION

The field of the invention relates to cancer therapy and, morespecifically, to compositions and methods for diagnosing, treating, andmonitoring cancer in an individual patient. In addition, the inventionrelates to compositions and methods for patient-specific cancergenomic/proteomic analysis, genetic network inference, prediction oflarge-impact key network connector nodes, node-targeted patient-specifictreatment, and integrated clinical and post-perturbationloss-of-function assessment in an individual cancer patient.

REFERENCE TO A SEQUENCE LISTING

The present application includes a Sequence Listing, which has beensubmitted in ASCII format via EFS-Web and is hereby incorporated byreference in its entirety. Said ASCII copy, created on Oct. 31, 2013, isnamed GRAD:1008CON2 txt and is 15 KB in size.

BACKGROUND OF THE INVENTION

While modern chemotherapeutic drugs provide patients with an establishedbut variable and non-predictable means of combating cancer growth,invasion and metastasis, such drugs have significant limitations anddrawbacks. For example, it is well-known that modern chemotherapeuticdrugs are generally non-specific in their mechanism of action. That is,such drugs are non-discriminatory in that they preferentially targetproliferating over quiescent cells-rather than cancer over normal cells.It is therefore not surprising that traditional chemotherapeutics havecompromised efficacy due to the narrow window betweentherapeutically-effective and toxicity-producing concentrations.

Using rapidly emerging technologies and associated methodologiesdeveloped over the last decade, research efforts have actively pursuedthe development of agents that target specific abnormal genes, cancerphenotype-related amplified genes, and over-expressed oncogene proteinscommonly found in human tumors. These methods may be roughly dividedinto 2 classes: 1) monoclonal antibodies and/or small moleculeinhibitors targeted against the inappropriately expressed orover-expressed protein (e.g., tyrosine kinase inhibitors,farnesyltransferase inhibitors, etc.) and 2) manipulations of thetranscriptosome machinery itself to suppress the production of theseproteins (e.g., antisense, siRNAs, etc.). The second method, that ofactually altering production of the oncogene product, for example,entails specific gene-silencing via suppression of expression levels oftargeted mRNA or modulation of the stability and/or translationalactivity of targeted mRNA.

While targeted therapies have demonstrated efficacy in both pre-clinicaland clinical applications, such approaches have exhibited significantlimitations. The drawbacks of such approaches are caused by therobustness of the co-opted cancer biome. Indeed, cancer cellproliferation and survival is not the result of single, linear proteininteractions, but rather the result of interconnected network pathways(with multiple feedback loops) of protein/gene activation. Therobustness of this system endows the cancer with functional stability.Therefore, it is not surprising that interventions against a randomsingle cellular target would have only limited effect on the malignantphenotype. That is, despite the application of targeted therapeutics inpatients with gene amplification and/or over-expressed protein kinases,for example HER 2 and EGFR, respectively, the presence of functionalredundancy in a robust cancer pathway network (from the genome throughthe proteome and metabalome, inclusively) is likely to “buffer” theeffect of random single gene or protein-product knock-out on themalignant process. In addition, nearly 200,000 possible protein signalsand 50,000 mRNA signals are known to be operating in any given cancercell, and an expanding number of ncRNAs (non-coding RNAs) are beingreported that modulate the cancer process by promoter selection,alternate splicing, RNA editing and mRNA stability. These signals arelargely independent of cancer morphology and are reformatted as modifiedvectored edges (links) in an evolved co-opted hierarchical modular powerlaw network which, by the very nature of its robustness, expose fragilecritical molecular pathways on which cancer cell proliferation andsurvival depend.

In light of the foregoing, there is a demand for a process that enablesthe selection of such fragile pathway (signature) signals unique to thecancer cells in an individual patient. Such process would allow forselectively effective therapeutic management of the patient or patientpopulations (with similar signals). Still further, there is a demand forcompositions and methods that enable physicians to target and modulatethe expression of malfunctioning genes and destroy the cancer cellsharboring the same (as opposed to merely targeting and destroyingproliferating cells) that are implicated in the molecular pathways thatare critical to cancer cell survival and/or proliferation. Preferably,such compositions and methods are tailored to the unique, abnormal geneexpression identified in the cancer cells of each individual patient.

SUMMARY OF THE INVENTION

According to a first embodiment of the present invention, methods fortreating cancer are provided, which comprise (a) obtaining a specimen ofcancer tissue from a patient; (b) obtaining a specimen of normal tissuein the proximity of the cancer tissue from such patient; (c) extractingtotal protein and RNA from the cancer tissue and normal tissue; (d)obtaining a proteomic profile of the cancer tissue and normal tissueusing 2D difference in-gel electrophoresis/mass spectrometry(2D-DIGE/MS); (e) identifying proteins that are over-expressed in suchcancer tissue compared to normal tissue; (f) obtaining a normalizedgenomic profile of the cancer tissue and normal tissue using microarraytechnology; (g) comparing the expression profile of the cancer tissue tothat of the normal tissue; (h) prioritizing proteins (and the genesencoding such proteins) with coupled over-expression that are eitherpreviously identified as cancer-related genes or in one of sixfunctional groups postulated as foundational to the cancer process; (i)designing an appropriate RNA interference (RNAi) expression cassette to,directly or indirectly, modulate the expression of the genes encodingthe prioritized proteins; (j) incorporating said cassette into anappropriate delivery vehicle; (k) providing the patient with aneffective amount of the delivery vehicle to, directly or indirectly,modify the expression of such genes exhibiting abnormal expressionlevels; (l) assessing the molecular activity-based reduction in cellularand potentially plasma levels of the targeted gene(s) after exposure totreatment (i.e., the delivery vehicle); and (m) pursuing subsequenttreatment, if necessary, based on the emergence of new priority genesand over-expressed cancer-related proteins.

In other embodiments, target gene expression may be repressed in thetumor and, therefore, require derepression or exogenous supplementationin order to achieve a therapeutic benefit to the patient. Upregulationof gene expression may be achieved by supplying additional gene copy tothe tumor cell, wherein said gene copies are insulated from therepressive effect being exerted on the endogenous gene expression. Inother cases, the repressive element that suppresses the target geneexpression may itself become a target for knock-down or suppressive RNAitherapy. In still other cases, the repressive element may beout-competed by exogenously supplied analogs or gene expression elementsthat produce such analogs. In the foregoing embodiments, the repressedtarget gene may be normalized or upregulated (derepressed) using, forexample, zinc finger proteins (ZFP), RNA activation (RNAa), or miRNAmodulation in linkage with or in a common vector.

The invention further provides that cancer/normal tissue whole genomicanalysis may be employed to ascertain an index patient's geneticpredisposition to a particular cancer as well as a toxicogenomicdisplay, wherein such analysis may include determining the copy number,structure, location, and sequence of a particular gene (or collection ofgenes). Such DNA genomic analysis may be carried out using varioustechniques well-known in the art, including without limitationchromosomal karyotyping, fluorescence in situ hybridization (FISH) (forgene copy number determination), high resolution genetic footprinting(for protein-DNA interactions), restriction fragment length polymorphism(RFLP) analysis, single nucleotide polymorphism analysis, andhigh-throughput DNA sequencing (for gene structural features andmutations).

According to further embodiments of the present invention, geneexpression profile information (and/or proteomic information) isprovided to a computing platform which assists in assessingco-expression and pathway/module ascription (and, using established andexpanding databases, assessing co-regulation by common transcriptionfactors), as well as identification of genes exhibiting abnormalexpression levels and/or patterns, which, when correlated, may representpreferred targets for RNAi therapy (as described herein).

According to still further embodiments of the present invention, certainkits and compositions are provided that may be used for carrying out themethods of diagnosing, treating, and monitoring cancer described herein.

The above-mentioned and additional features of the present invention arefurther illustrated in the Detailed Description contained herein. Allreferences disclosed herein, including U.S. patents and published patentapplications, are hereby incorporated by reference in their entirety asif each was incorporated individually.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1A and 1B show: FIG. 1A is a flow diagram showing certain methodsof the personalized therapeutic programs described herein. FIG. 1B is aflow diagram showing the various molecular and phenotypic data typesthat are utilized by certain methods encompassed by the inventiondescribed herein.

FIGS. 2A and 2B show: FIG. 2A is a diagram illustrating the cellularprocessing of the enhanced shRNAs encompassed and employed by thepresent invention. FIG. 2B is a diagram illustrating two RNAi pathways.

FIGS. 3A and 3B show an analysis of 2-D DIGE images using DeCyderSoftware and mass spectrometry protein identification. The upper leftpanel shows the protein expression pattern of a normal lymph node fromPatient-1 following 2-D gel electrophoresis. The upper middle panelshows the protein expression pattern of a malignant lymph node fromPatient-1. The upper right panel shows a 2-D gel electrophoresis imageshowing the protein expression pattern of a normal lymph node (labeledwith Cy3 (green)) superimposed over a 2-D gel electrophoresis imageshowing the protein expression pattern of a malignant lymph node(labeled with Cy5 (red)). Circles indicate protein spots withsignificant expression level changes. The middle panel shows acomputer-generated 3D view of one protein spot change between the normaland malignant lymph nodes shown in the upper right panel. The lowerpanel shows the results of mass spectrometry analyses that weresubsequently performed on certain proteins (exhibiting an increase inexpression level in the malignant lymph nodes) excised from the 2-D gelas described herein. The mass spectrometry analysis identified thesubject protein as RACK1.

FIGS. 4A to 4C show 2-D gel electrophoresis images showing the 16proteins described herein that were determined to be more than 2-foldover-expressed in malignant tissue (bright red) relative to normaltissue (as determined by mass spectrometry analysis). FIG. 4A shows acomparison of non-malignant tissue to malignant tissue on Mar. 9, 2005.FIG. 4B shows a comparison of non-malignant tissue to malignant tissueon Jan. 26, 2006. FIG. 4C shows a comparison of malignant tissue fromJan. 26, 2006 to malignant tissue from Mar. 9, 2005. The circled areasin panels A and B represent the prioritized proteins that were selectedfor further analysis, as described herein.

FIGS. 5A to 5C show the following: FIG. 5A was prepared using VisualCellsoftware that show “nearest neighbor protein-protein (first order)interactions” of the 5 prioritized proteins described herein. FIG. 5B isa diagram showing “second order interactions” for Stathmin1 (SDCBP).FIG. 5C is a diagram showing “second order interactions” for RACK1(GNB2L1).

FIG. 6: Immunohistochemical staining of Patient-1 tumor cells inmalignant tissue biopsied from Jan. 26, 2006.

FIGS. 7A to 7C show the following: FIG. 7A shows a Western blotdemonstrating upregulated expression of RACK1 in Patient-1 malignanttissue and malignant cell line CCL247. Limited expression in normaltissue for Patient-1 (lymph node shown, skin and peripheral blood cellsalso negative) is also shown for comparison. FIG. 7B shows Western blotsshowing siRNA knockdown of RACK1 in “mock” (i.e., control) samples (lane1), 24 hour post-siRNA (post-siRACK) knock-down (lane 2), and 48 hourpost-siRACK knock-down (lane 3). FIG. 7C is a chart showing “cell kill”in response to siRNA-RACK 1 over time in colon cancer cell line CCL247.

FIGS. 8A and 8B show as follows: FIG. 8A show the differential geneexpression analysis in malignant tissues (collected on Mar. 9, 2005,tumor tissue #1; Jan. 26, 2006, tissue #2) and normal tissue from thesame patient. FIG. 8A show the relative expression of highly-connectedpriority protein mRNAs in malignant and non-malignant specimens.

FIG. 9: Table of the “prioritized” proteins discussed in the Examplesbelow.

FIGS. 10A and 10B show a list of nucleic acid sequences used toconstruct certain enhanced shRNA molecules described herein, which showsthe location of the sense sequence, anti-sense sequence, and mismatchesthereof.

FIGS. 11A to 11E show as follows: FIG. 11A shows a predicted stem-loopstructure of Construct 15/16. FIG. 11B shows a predicted stem-loopstructure of Construct 17/18. FIG. 11C to 11E show a predicted-stem loopstructures of Constructs 54/18, 55/18, and 56/18, respectively, whichcontain mismatches and bulges either within the sense or anti-sensestrand.

FIG. 12: A diagram showing the pSilencer 4-1 Neo vector described in theExamples below.

FIG. 13: A diagram of the psiTEST-STMN1 vector containing the STMN1 cDNAinsert described herein.

FIG. 14: Charts illustrating the reliability of the reporter-cDNAtranscription fusion system used in the Examples below, which involvedHEK-293 cells co-transfected with psiTEST/STMN1 and various shRNAconstructs.

FIG. 15: A chart illustrating RNA knock-down by psiTEST/STMN1-alone andenhanced shRNAs in transfected cells over a period of time.

FIG. 16: (Top) An image showing Western blot results of the STMN1protein. (Bottom) A bar graph illustrating STMN1 RNA knock-down byConstructs 15/16 and 17/18 at different concentrations.

FIG. 17: Flow cytometry results showing the effect of Construct 15/16and Construct 17/18 on STMN1 expression.

FIG. 18: A bar graph summarizing the cell death assays described hereinfor the enhanced shRNA-transfected cells described in the Examplesbelow, wherein STMN1 protein expression was suppressed by such enhancedshRNAs.

FIG. 19: A bar graph showing the reduction in STMN1 mRNA following theintroduction of the enhanced shRNA molecules described in the Examplesbelow.

FIG. 20: A bar graph summarizing the results of flow cytometry analysis,which shows the percentage of STMN1-positive cells detected followingthe introduction of the enhanced shRNA molecules described in theExamples below.

FIGS. 21A and 21B are flow chart summarizing the process by which theGNS system, described herein, assists in identifying target genes (andprioritized proteins) for RNAi knock-down.

FIGS. 22A-1 through 22A-4; FIGS. 22B-1 through 22B-3; FIGS. 22C-1through 22C-3; FIGS. 22D-1 through 22D-3; FIGS. 22E-1 through 22E-3;FIGS. 22F-1 through 22F-2; and FIGS. 22G-1 through 22G-6; show theresults of nearest neighbor protein-protein (first order) interactionsof priority proteins in VisualCell of seven (7) patients that wereexamined using the methods described herein.

BRIEF DESCRIPTION OF THE SEQUENCE LISTING

SEQ ID NO:1-3 represent gene-specific PCR primers used to prepare thecDNAs described herein.

SEQ ID NO:4 represents the sense strand of the siRNAs used to suppressthe expression of STMN1 (#16428).

SEQ ID NO:5 represents the antisense strand of the siRNAs used tosuppress the expression of STMN1 (#16428).

SEQ ID NO:6 represents the psiTEST Forward PCR primer.

SEQ ID NO:7 represents the psiTEST Reverse PCR-primer.

SEQ ID NO:8 represents the pSilencer Forward PCR primer.

SEQ ID NO:9 represents the pSilencer Reverse PCR primer.

SEQ ID NO:10-22 represent the sequences used to prepare the enhancedshRNA constructs described herein, and summarized in Table 1 below.

SEQ ID NO:23 represents the sense strand of the RACK1 siRNA moleculesdescribed herein.

SEQ ID NO:24 represents the antisense strand of the RACK1 siRNAmolecules described herein.

SEQ ID NO:25 represents the RACK1 gene.

SEQ ID NO:26 represents the Syntenin gene.

SEQ ID NO:27 represents the Stathmin 1 gene.

SEQ ID NO:28 represents the sense strand of the Stathmin 1 siRNA.

SEQ ID NO:29 represents the antisense strand of the Stathmin 1 siRNA.

SEQ ID NO:30 represents the sense strand of the Syntenin siRNA.

SEQ ID NO:31 represents the antisense strand of the Syntenin siRNA.

DETAILED DESCRIPTION OF THE INVENTION

The following will describe in detail several preferred embodiments ofthe present invention. These embodiments are provided by way ofexplanation only, and thus, should not unduly restrict the scope of theinvention. In fact, those of ordinary skill in the art will appreciateupon reading the present specification and viewing the present drawingsthat the invention teaches many variations and modifications, and thatnumerous variations of the invention may be employed, used, and madewithout departing from the scope and spirit of the invention.

According to a first embodiment of the present invention, methods fortreating cancer are provided (FIG. 1A), which comprise (a) obtaining aspecimen of cancer tissue from a patient; (b) obtaining a specimen ofnormal tissue in the proximity of the cancer tissue from such patient;(c) extracting total protein and RNA from the cancer tissue and normaltissue; (d) obtaining a proteomic profile of the cancer tissue andnormal tissue using 2D difference in-gel electrophoresis/massspectrometry (2D-DIGE/MS); (e) identifying proteins that areover-expressed in such cancer tissue compared to normal tissue; (f)obtaining a normalized genomic profile of the cancer tissue and normaltissue using microarray technology; (g) comparing the expression profileof the cancer tissue to that of the normal tissue; (h) prioritizingproteins (and genes encoding such proteins) with coupled over-expressionthat are either previously identified as cancer-related genes or in oneof six functional groups postulated as foundational to the cancerprocess; (i) designing an appropriate RNA interference expressioncassette to, directly or indirectly, modulate the expression of suchgenes; (j) incorporating said cassette into an appropriate deliveryvehicle; (k) providing the patient with an effective amount of thedelivery vehicle to, directly or indirectly, modify the expression ofsuch genes exhibiting abnormal expression levels; (l) assessing themolecular activity-based reduction in cellular and potentially plasmalevels of the targeted gene(s) after exposure to treatment (i.e., thedelivery vehicle); and (m) pursuing subsequent treatment, if necessary,based on the emergence of new priority genes and over-expressedcancer-related proteins. A non-limiting, preferred embodiment of suchmethods is illustrated in FIG. 1A. As used herein, the “six functionalgroups postulated as foundational to the cancer process” consist ofcancer cell survival, angiogenesis, self-sufficiency in growth signals,insensitivity to anti-growth signals, limitless replicative potential,and invasiveness (and metastagenicity).

The invention further provides that cancer/normal tissue whole genomicanalysis may be employed to ascertain an index patient's geneticpredisposition to a particular cancer, as well as a toxicogenomicdisplay, wherein such analysis may include determining the copy number,structure, location, and sequence of a particular gene (or collection ofgenes). Such DNA genomic analysis may be carried out using varioustechniques well-known in the art, including without limitationchromosomal karyotyping, fluorescence in situ hybridization (FISH) (forgene copy number determination), high resolution genetic footprinting(for protein-DNA interactions), restriction fragment length polymorphism(RFLP) analysis, single nucleotide polymorphism analysis, andhigh-throughput DNA sequencing (for gene structural features andmutations).

According to further embodiments of the present invention, geneexpression profile information (and/or proteomic information) isprovided to a computing platform which assists in assessingco-expression and pathway/module ascription (and, using established andexpanding databases, assessing co-regulation by common transcriptionfactors), as well as identification of proteins (and genes encoding suchproteins) exhibiting abnormal expression levels and/or patterns, whichmay represent preferred targets for RNAi (using, for example, thesiRNAs, conventional shRNAs, or enhanced shRNAs described herein).

According to still further embodiments of the present invention, certainkits and compositions are provided that may be used for carrying out themethods of diagnosing, treating, and monitoring cancer described herein.

Tissue Isolation

Normal and malignant tissue may be isolated from a patient usingstandard and well-known biopsy procedures. In certain preferredembodiments, however, such tissue may be processed using laser capturemicrodissection (LCM). The majority of tumor samples represent anadmixture of different cell types, including hematologic and vascularintercalated stromal tissue. Therefore, reported gene expressionpatterns may not be specific to malignant cells. This potentiallyconfounding factor may be addressed with the use of LCM technology.

LCM allows malignant cells to be selectively dissected and captured fromthe mixed population of cells found in a tumor biopsy, so that only amorphologically homogeneous population of cells is investigated from acomplex tissue. Improvements in nucleic acid amplification and proteindetection technologies have made it possible to accurately andreproducibly analyze small amounts of DNA, RNA, or proteins fromLCM-derived cells.

Accordingly, the invention provides that LCM may be used to separatemalignant from normal cells-followed by amplification in order to carryout the methods described herein and identify those genes differentiallyexpressed in a particular patient's tumor.

Nucleic Acid Extraction

Nucleic acids, such as RNA and/or DNA, may be isolated and purified fromcells, tissues or fluids of a patient using readily-available andwell-known procedures. For example, RNA may be preferentially obtainedfrom a nucleic acid mix using a variety of standard procedures (see,e.g., RNA Isolation Strategies, pp. 55-104, in RNA Methodologies, Alaboratory guide for isolation and characterization, 2nd edition, 1998,Robert E. Farrell, Jr., Ed., Academic Press). Additionally, RNAisolation systems/kits are available from numerous commercial vendors,such as the RNAqueous™, Phenol-free Total RNA Isolation Kit offered byAmbion (Austin, Tex.) or the PicoPure RNA Isolation kit offered byArcturus Bioscience (Mountainview, Calif.). Similarly, DNA isolationsystems/kits are readily available, such as the GeneElute™ MammalianGenomic DNA Miniprep Kit or GeneElute™ Blood Genomic DNA Kit offered bySigma-Aldrich Company (St. Louis, Mo.).

In certain preferred embodiments of the present invention, total RNAand/or DNA is extracted from LCM-isolated tissues. RNA and/or DNAextraction from LCM samples is a standard operation. It is generallypreferred to obtain about 20,000 cells and for gene expression profilesto be conducted for each cancer and normal tissue type.

In certain embodiments, for example, RNA may be extracted fromLCM-isolated tissues (or tissues obtained through conventional biopsyprocedures) using the PicoPure RNA Isolation kit referencedabove-according to the manufacturer's protocol. Quality of captured RNAis, preferably, examined following extraction. The quality of isolatedRNA may be measured using well-known procedures, such as with an Agilent2100 Bioanalyzer and RNA 6000 Pico LabChips (Agilent Technologies, PaloAlto, Calif.). The isolated RNA is preferably divided into separategroups of equal proportion, such as two or more groups, which are thensubjected to parallel RNA amplification and gene profile analysis. It isgenerally preferred that R-square tests be performed to provide anindicator for the reproducibility of the data generated from suchdifferent groups of isolated RNA.

In certain preferred embodiments of the present invention, the isolatedRNA (and/or DNA) is amplified before labeling (and subsequent geneexpression profiling or other nucleic acid analysis described herein).Those of ordinary skill in the art will appreciate that RNA and DNAamplification (and labeling) may be carried out usingcommercially-available kits and/or well-known procedures. For example,RNA amplification may be carried out using a RiboAmp RNA AmplificationKit (Arcturus Bioscience, Mountainview, Calif.). Following suchamplification step, the quality of the amplified RNA (and/or DNA) is,preferably, examined with BioAnalyzer—wherein, for example, the sizedistribution of amplified RNA should be a healthy streak larger than 250nucleotides (nt) in size. Next, the amplified RNA (and/or DNA) may belabeled with appropriate isotopes, chemoluminescent molecules, and otheragents using well-known techniques and/or commercially-available kits.

Gene Expression Profiling & Other Nucleic Acid Analysis

RNA (cDNA) expression profiles of the isolated cancer and normal cellsmay be obtained using readily-available technology, such as microarraytechnology. In recent years, “DNA chips” have provided a reliable meansfor measuring the expression levels of particular genes or, moreparticularly, the level of specific mRNA transcripts (or cDNAs) in asample. Of course, those skilled in the art will appreciate that othermethods may be employed to obtain such expression profiles, such asquantitative PCR (qPCR), northern blots, and others (currently-availableor discovered hereafter).

In certain preferred embodiments of the present invention, for example,microarray analysis may carried out using the GeneChip® system ofAffymetrix following recommended procedures. Still more specifically,for example, such microarray analysis may be carried out using theAffymetrix Human U133 Plus 2.0 GeneChip®, which may be used forhybridization and analysis of the isolated, amplified, and labeled RNAdescribed herein. Hybridization and processing of such GeneChip may beperformed using the automated GeneChip Instrument System. Dataacquisition, sample normalization, and initial data analysis may beperformed with Affymetrix Microarray Suite (MAS) software.

Preferably, the data collected from such microarray analysis areimported into a computing environment, wherein software and other toolsmay be used to analyze and interpret such data. In certain embodiments,for example, such data may be directly imported into GeneSpring 7.0 geneexpression analysis software (Silicon Genetics, Redwood City, Calif.)for expression profile analysis. The RNA expression profile of normaland malignant cells may then be analyzed, preferably, in pair-wisefashion to identify genes that are significantly overexpressed, forexample, in the malignant cells (when compared to the correspondingexpression level of particular gene(s) in the normal cells). In certainpreferred embodiments, the quality of data will also be determined. Forexample, robust data that reveal significant differentialgene-expression patterns (between normal and cancer cells) may befurther analyzed at a higher level for target identification. In suchembodiments, the raw data will be transported to a computational system,such as the system designed and owned by Gene Network Sciences, Inc.(GNS, www.gnsbiotech.com)—as described herein. The system employed byGNS to identify abnormally expressed genes and Target Genes (as definedherein) is described in U.S. Patent Application Publications2003/0144823 (Scale-free Network Inference Methods); 2004/0243354(Systems and Methods for Inferring Biological Networks); and2004/0088116 (Methods and systems for creating and using comprehensiveand data-driven simulations of biological systems for pharmacologicaland industrial applications), all of which are expressly incorporatedherein by reference.

As previously described, the invention further provides that DNA genomicanalysis may be employed in addition to (or in replacement of) geneexpression profiling. Such analysis may be employed to, for example,assess co-expression (i.e., genes with similar mRNA expression profiles)and pathway/module ascription (and, using established and expandingdatabases, assessing co-regulation by common transcription factors), aswell as identification of genes exhibiting abnormal expression levelsand/or patterns which, when correlated, may represent preferred targetsfor RNAi. Additionally, DNA genomic analysis may be conducted toascertain a patient's genetic predisposition to a particular cancerand/or the current disease state of such patient, wherein such analysismay include determining the copy number, structure, location, andsequence of a particular gene (or collection of genes). This may alsoinclude a toxicogenomic display to enhance the understanding ofmechanisms of toxicity and provide a potential pre-exposure screeningfor risk of therapy-related adverse events and characterization thereof,especially for trans-modality combination therapy, e.g., a targetedshRNA and a selected chemotherapy agent.

Such DNA genomic analysis may be carried out using various techniqueswell-known in the art, including without limitation chromosomalkaryotyping, fluorescence in situ hybridization (FISH) (for gene copynumber determination), high resolution genetic footprinting (forprotein-DNA interactions), restriction fragment length polymorphism(RFLP) analysis, single nucleotide polymorphism analysis, and highthroughput DNA sequencing (for gene structural features and mutations).The results and information obtained from such DNA genomic analysis are,preferably, imported into a computing environment, wherein software andother tools may be used to analyze and interpret such data. Theinvention provides that such information may be considered (preferably,in connection with gene expression profile and/or proteomic information)when identifying Target Genes (as described herein).

Proteomics: 2D-DIGE/MS

Microarray technology is well established as a powerful tool for globalgene expression analysis. mRNA profiles (or cDNA profiles) have beenused both for cancer classification as well as to predict prognosis.Whereas the mRNA (cDNA) microarray studies have greatly enhanced ourunderstanding of the underlying mechanisms of cancer, studies at theprotein level also present unique advantages, as proteins are the directeffectors of cellular behavior. Furthermore, the invention provides thatbecause of post-translational modifications ncRNA modulated effects,including alternate RNA splicing, RNA editing and mRNA stability, andquantitative sampling limitations (such as serum), the isolated cancerand normal tissue in each patient are, preferably, analyzed usingproteomic approaches.

While such proteomic approaches may be carried out using methodswell-known to those of ordinary skill in the art, the invention providesthat, in certain embodiments, such approach may be carried out using2D-DIGE/MS analysis of protein extracted from patient tissue, i.e.,normal and cancer tissue (LCM-captured if <70% cancer cells).Preferably, duplicate samples will be selected for reproducibilitycomparison.

In certain embodiments, the 2D-DIGE system may be optimized to identifyapproximately 10,000 protein spots-using combinations of smaller pHranges for isoelectric focusing (IEF) separation, and variablepercentage sodium dodecyl sulfate (SDS) gel electrophoresis separation.With the resolution of 10,000 protein spots, the 2D-DIGE/MS analysissystem provides yet further information that may be used in identifyingTarget Genes (defined herein) and corresponding RNAi molecules asdescribed herein. Preferably, the information provided by the 2D-DIGE/MSanalysis will be used in connection with (and compared to) theinformation provided by microarray analysis when identifying TargetGenes and corresponding RNAi molecules as described herein.

In certain non-limiting embodiments of the present invention, 2D-DIGE/MSanalysis may be carried out by isolating approximately 10 mg-equivalentof human normal and cancer tissues or, alternatively, capturing asufficient amount of such tissues using laser capture microdissection(LCM). Next, such tissue may be lysed in 2-D lysis buffer containing 30mM Tris-HCl (pH 8.8), 7 M urea, 2 M thiourea and 4% CHAPS. Sonicationmay be used to facilitate the lysis step. The protein lysates may, ifnecessary, be further purified using filters, chromatography, or othermeans. The sufficiently purified protein isolates may then be labeledwith, for example, CyDye fluors (Cy2, Cy3 or Cy5) for 30 minutes at0[deg.] C.—using procedures well-known in the art orcommercially-available kits. In such example, the reaction may beterminated with the addition of lysine, and samples to be compared aremixed in an equal molar ratio. Next, in such example, destreak solutionand rehydration buffer may be added (100 [mu]l each) before samples areloaded onto a 13-cm IPG strip, with a linear pH range of 3-10, for IEFanalysis (1<st> Dimension) (GE Healthcare, formerly AmershamBiosciences, Piscataway, N.J.).

After the IEF analysis is completed, the IPG strip is incubated withSDS-containing equilibration solutions and placed on top of a 9-12%gradient SDS gel (18*16 cm, 1-mm thickness). Electrophoresis separationwith the SDS gel is performed at 16[deg.] C. (2<nd> Dimension). Afterelectrophoresis, the gel is analyzed using an appropriate scanner, suchas a Typhoon Trio scanner (GE Healthcare), and the images may beanalyzed using ImageQuant and DeCyder software. Protein spots ofinterest are excised from the gel and protein IDs are determined usingmatrix-assisted laser desorption/ionization time-of-flight massspectrometry (MALDI-ToF). Data obtained from 2D-DIGE/MS will be comparedto data obtained from microarray. Non-limiting examples of the data, andanalysis thereof, produced by the foregoing process are shown in FIG. 3.The differentially-expressed proteins identified by the above proteomicanalysis will be provided to and used in the pathway identification andTarget Gene selection process described herein.

Target Gene Selection

High-quality raw data from the foregoing gene expression profiling(e.g., microarray analysis), genomic DNA analysis, and/or proteomic(e.g., 2D-DIGE/MS) analysis will be stored and analyzed with acomputational system, such as the system designed and owned by GNS, toidentify Target Genes. As used herein, “Target Gene” refers to a nucleicacid sequence in a cancer cell, wherein the expression of the sequenceis specifically and effectively modulated using the methods of thepresent invention. Preferably, the Target Gene is shown to be implicatedin the growth (proliferation), maintenance (survival), and/or migratory(metastatic) behavior of an individual's cancer. Furthermore, the terms“prioritized proteins,” “priority proteins,” and like terms refer to theproteins encoded by such Target Genes. Non-limiting examples of resultsshowing the identification and analysis of various Target Genes found inseveral patients, using the methods described herein, are shown in FIGS.22A-1 through 22A-4; FIGS. 22B-1 through 22B-3; FIGS. 22C-1 through22C-3; FIGS. 22D-1 through 22D-3; FIGS. 22E-1 through 22E-3; FIGS. 22F-1through 22F-2; and FIGS. 22G-1 through 22G-6.

In certain preferred embodiments of the present invention, Target Geneselection may be based on one or more of the following criteria: (1)high cancer expression compared to low normal expression (i.e., therelative magnitude of the difference in expression levels between aparticular gene in normal versus malignant cells); (2) key generegulatory (static) nodes in dominant activated cancer associatedpathways (e.g., the role of akt and mTOR in the ras activated pathway);(3) whether a particular gene represents a strategic connecting(dynamic) node shared by multiple cancer signal transduction pathways;(4) known cancer-related genes (to name a few, genes such as HER2 (agrowth factor receptor), ras (a signal transduction molecule), myc (atranscription factor), src (a protein tyrosine kinase), and Bc1-2 (ananti-apoptotic molecule); and (5) co-essential genes characterized bylow k-robustness the concomitant repression of which overcomes theeffect of functional gene duplication (i.e., genetic redundancy)).

As described herein, the invention provides that, in addition to anindividual's gene expression profile, other information may beconsidered when identifying Target Genes. For example, the inventionprovides that the results and information obtained from DNA genomicanalysis may be considered during Target Gene selection. That is, suchDNA genomic analysis may reveal whether a patient carries a particularmutation in one or more genes (and/or whether such one or more genesexhibit abnormal gene structure, location, and/or copy number), whichare known or suspected to be implicated in cancer growth, maintenance,migratory behavior, etc. For example, based on the results of such DNAgenomic analysis (and information that it provides relating to thegenetic aberrations, if any, detected in a particular individual), itmay be desirable to select a Target Gene(s) that may correct or mitigatethe effects of such genetic aberrations.

Still further, Target Gene selection may consider whether the nucleicacid sequence of a candidate gene exhibits RNAi sensitivitycharacteristics, e.g., genes that have been reported to be effectivelyknocked-down by RNAi mechanisms (or whether the expression of suchnucleic acid may be effectively modulated using, e.g., othertranscriptional and/or translational inhibitors). This approach isconceptually consistent with the rationale proposed for the use of RNAi,for example, to evaluate the genetics of synthetic lethality. Theforegoing criteria may be used by computational systems, such as thesystem designed and owned by GNS, to assist in the identification ofTarget Genes.

The invention provides that, despite the evolved robust survivaladvantage of cancer cells (due, in large part, to their co-option ofnormal pathways), sites of fragility resulting from functional tradeoffsaccompanying the evolution of the co-opted biomic network result in“addiction” to a limited set of functional pathways with key regulatorycores of single or multiple genes required for said survival. Thepresent invention, preferably, exploits such dependency as the “Achillesheel” of cancer.

In certain embodiments of the present invention, the gene expressionprofiles of normal and cancer tissues are compared over a non-selective,broad range of coding sequences. In other, preferred embodiments, suchcomparison is focused on a number of genes that have been shown to beimplicated, directly or indirectly, in cancer. Preferably, the identityand sequences of such genes are constantly updated to reflect andincorporate new information that is generated in cancer research. Forexample, in certain embodiments of the present invention, the analysisof gene expression profiles of normal and cancer cells are made byconferring with a database, which contains a listing of all such genesthat are known to be implicated in cancer at the time of such analysis.Preferably, such database is capable of being regularly updated toreflect the most current understandings of cancer and causes thereof, sothat the expression levels of all (or a significant number of) relevantgenes may be analyzed.

In certain embodiments, the expression levels of the genes analyzed inan individual's cancer tissue are compared to the expected levels inpopulation-derived cancer and normal tissue, wherein such expectedvalues are stored in a database and based on previous research. Inother, preferred embodiments of the invention, the expression levels ofthe genes analyzed in an individual's cancer tissue are compared to thecorresponding levels actually measured in normal tissue. The inventionprovides that by comparing the expression profiles of cancer and normaltissue extracted from the same patient, the individual nuances andexpression aberrations that each individual patient may carry arenormalized. By co-analyzing the personal data in the context ofavailable population-derived data, the invention allows for thevalidation of the latter, while benefiting from enhanced discovery inthe targeted data set through the recognition of conservation acrossmultiple gene sets otherwise limited in any one gene set.

In some cases, the Target Genes may be expressed at significantly higherlevels when compared to normal tissue from the same patient (orpredicted levels based on public literature). In such cases, it may beappropriate to build an expression cassette that expresses an shRNA ormultiple shRNAs, for example, which hybridize(s) to the targeted mRNAtranscript or multiple targeted mRNA transcripts encoded by such TargetGenes, and reduces the expression levels of such Target Gene or Genessimultaneously-either at transcriptional and/or at translational levels.Similarly, the invention provides the utilization of small interferingRNA (siRNA) to achieve the above-mentioned repression of Target Geneexpression. Furthermore, siRNA and shRNA may be applied in combinationto achieve the maximum and desirable modulatory effect that is the mostadvantageous for the intended therapeutic applications. Still further,the invention provides certain novel enhanced shRNA molecules that maybe employed to modulate the expression of such Target Genes, asdescribed herein.

In still other embodiments, the expression levels of the Target Genesmay be undesirably repressed. In such cases, multiple mechanisms,including but not limited to microRNA (miRNA), ncRNA,aberrantly-expressed transcription factors and/or transcriptionalregulatory elements, may cause a corresponding reduced expression levelfor the Target Gene (referred to herein as the “Contributing Gene”). Forexample, the invention provides that the over-expression (or increasedcopy number) of a Contributing Gene (e.g., a sequence encoding atranscriptional repressor) may, directly or indirectly, cause a TargetGene to exhibit an undesirable reduced expression level. In suchembodiments, appropriate siRNA and/or shRNA cassettes, for example, maybe constructed to reduce the expression level of the Contributing Gene,thereby decreasing the negative selective pressure on the Target Gene(and, preferably, allowing the expression level of the Target Gene toresume to normal or preferred levels). Similarly, it may be desired tointroduce additional or other cassettes that encode preferredtranscriptional and/or translational modifiers or inhibitors—to modulatethe expression of such Contributing Gene (thereby regulating theexpression of the Target Gene).

In yet other cases, the expression levels of a Target Gene may berepressed (e.g., suppressor gene) and, via connectivity, be in causalrelationship with overexpressed Target Genes. In such cases, saidrepressed Target Gene may be normalized or upregulated (derepressed)using zinc finger proteins (ZFP), RNA activation (RNAa), or miRNAmodulation in linkage with or in a common vector with the invention. Instill other cases, the repression may be overcome by supplying exogenouscopies of the Target Gene, wherein said gene copies are insulated fromthe repressive effect being exerted on the native (i.e., endogenous)gene expression. In still other cases, the repressive element may beout-competed by exogenously-supplied analogs or gene expression elementsthat produce such analogs.

The invention further provides that multiple siRNA and shRNAcombinations may be employed to suppress the expression of abnormallyhighly expressed Target Genes and Contributing Genes.

In certain embodiments, raw data obtained from gene expression profiling(e.g., microarray analysis), genomic DNA analysis, and/or proteomicanalysis (e.g., 2D-DIGE/MS) may be transported to a computer system fortemporary analysis, such as the proprietary computer system designed,developed and owned by Gene Network Sciences, Inc. (GNS,www.qnsbiotech.com)—which uses a certain Network Inference softwareplatform (FIGS. 21A and 21B). The system employed by GNS to identifyabnormally expressed genes and Target Genes (as defined herein) isdescribed in U.S. Patent Application Publications 2003/0144823;2004/0243354; and 2004/0088116-all of which are expressly incorporatedherein by reference.

The Network Inference software platform constructs a probabilistic modelof causal relationships between network components that is consistentwith a given constraining data set, such as high-throughput data frommicroarray analysis (FIG. 21A). Rather than identifying a single“best-fit” model, the probabilistic model incorporates uncertainty inthe data and allows the corresponding uncertainty in the predictions tobe quantified. Inferring regulatory relationships between genes is aglobal optimization problem in which the objective function to beminimized measures the difference between predictions of the networkmodel and the constraining experimental data. The search domain for thisglobal optimization is the discrete space of all possible bipartitegraphs that may be constructed out of an entity (mRNA, protein, orchemical levels) and interaction nodes. Each interaction node isassociated with a mathematical function that describes a quantitativerelationship between entity nodes. The ensemble of models generated isthen subject to analysis to extract out causal relationships. Theseinclude forward simulations on the ensemble of models generated thatenable the user to determine the response to new perturbations notexplicitly represented in the data set (FIG. 21B). For example, anensemble of models can be inferred from a data set that includes singlesiRNA or shRNA perturbations from many biological samples along with thecorresponding molecular profiling and phenotypic data. The simulationengine then enables the user to test out all two-way and three-waycombinations that synergistically lead to inhibition of the phenotypicend point. In this way, scientists may determine key molecular targetsand target combinations that significantly impact efficacy and/ortoxicity.

Edges in the network generated by the GNS optimization algorithm, forexample, correspond to direct causal relationships between measurednodes. Indirect causal relationships between measured nodes are mostlyeliminated by the algorithm because it employs a Bayesian scoringfunction that penalizes extra complexity. However, every edge mayrepresent an indirect relationship via unmeasured nodes (hiddeninteractions), such as protein signaling pathways that affect geneexpression. The Bayesian framework edges in the network may be eitherdirected or undirected (symmetrical). Connections between compounds(e.g., siRNAs), genes and phenotypic endpoints are directed, sincesiRNAs represent causal perturbations and molecular changes thatcausally influence the phenotypic response. The direction of gene-geneconnections can be elucidated using perturbation experiments, such asthrough shRNA- and/or siRNA-mediated gene silencing experiments. Thepresent invention may further utilize an experimental paradigm tovalidate predicted outcomes and to further contribute to a database (foruse in future predictions).

Networks learned from data using the GNS Network Inference platformcorrespond to causal relationships in the experimental system whereperturbations to particular genes from siRNAs, for example, arepredicted to result in downstream (or upstream in the case of feedbackloops as well as autoregulatory transcription factors) changesthroughout the network. The accuracy of the inferred networks cantherefore be validated by readily-available experimental techniques. Thegenes that appear in the neighborhood of siRNA (or shRNA) nodes in thenetwork carry the interpretation of being the genes the change inexpression of which (in response to siRNA and/or shRNA treatment) isexplained (in the Bayesian sense) by the uncovered network. These genestherefore correspond to potential biomarkers of siRNA/shRNA activity. Ifefficacy or toxicity endpoints are also measured, then these‘first-line’ genes in a network that connect siRNA/shRNA effects to theendpoint correspond to biomarkers of treatment efficacy or toxicity. Ifquantitative proteomics data (e.g., protein phosphorylation levels) areavailable in addition to data from cDNA microarrays, then the networkslearned by including these data types in the constraining data set mayuncover direct siRNA- or shRNA-protein relationships capable ofelucidating siRNA or shRNA mechanism of action at the protein level.Model predictions may be analyzed in the context of known pathwayinformation to aid in interpretation of results.

The majority of the databases currently available from human derivedbiopsies are mainly based on conventional compound-based geneperturbation models. Compound-based gene perturbation data are oftenconfounded by the potential side-effects (or additional effects) broughtabout by the interaction of said compound with other unintended targets.The present invention provides the further advantage of improvement ofthe database by utilizing said siRNAs or/and shRNAs to specificallyreduce expression of the intended Target Gene. Further advantages willbe envisioned by those of ordinary skill in art, based on theabove-mentioned combinatorial approach to developing and supplementing anovel database.

While the GNS computation analysis system provides a non-limitingexample of a platform that may be used to interpret the microarray,genomic DNA, and/or proteomic data described herein, each patient'scomparative malignant and normal gene-expression profiles, for example,may also be reviewed and interpreted manually-using a combination ofgene-expression analysis programs. Using the pathway viewer inGeneSpring, for example, the over-expressed genes and their expressionpatterns in an individual patient may be visually characterized based onthe location of such genes within a cellular pathway. In conjunctionwith the self-organizing clustering function of such software (orothers), the invention provides that the over-expressed genes andpathways may be mapped and interpreted. Additionally, protein levelcomparisons between cancer and normal tissues may be carried out usingthe procedures described above (and illustrated in FIGS. 3A and 3B).

Still further, Target Genes identified using any of the foregoingsoftware, platforms, or other means are, optionally, cross-referencedwith other appropriate databases, such as those databases maintained bythe Cancer Molecular Analysis Project (CMAP) site (cmap.nci.nih.gov) andthe BioCarta and KEGG pathways (cgap.nci.nih.gov) at NCI.

The invention provides that elevated mRNA levels, for example,identified in microarray analysis preferably correspond with discordantprotein expression observed in the proteomic analysis. If such analysesdo not correspond, a candidate Target Gene may still be a good candidatefor RNAi knock-down, but perhaps with lower priority. Withcomputer-assisted analysis, in certain embodiments, the inventionprovides that multiple Target Genes are preferably identified, such asat least five Target Genes, for each patient based on the variouscriteria described above. In such embodiment, the Target Gene selectionprocess may be augmented (or completely managed) by, for example, thedecision making process summarized in FIG. 1B (wherein an experimentalsystem is treated with compound(s), e.g., siRNA(s), to generatequantitative high-throughput data, whereby the platform uses the data tobuild a causal network connecting biological entities such as exogenoussiRNAs, mRNA, and/or protein and phenotype nodes).

Confirm Over-Expression of Selected Target Genes

Comparative gene expression levels of selected Target Genes arepreferably confirmed by quantitative RT-PCR methods. For example, totalRNA from normal and malignant patient tissue may be used for suchanalysis and comparison. Gene-specific PCR primers may be designed andchemically synthesized using well-known procedures or purchased from acommercial vendor. The primer sets will first be tested with total RNAisolated from tissue culture cells to establish appropriate PCRconditions. Once the appropriate PCR conditions are established and thespecificity of the primer set is validated, real-time RT-PCR may beperformed. Expression level for each Target Gene is, preferably,compared to a common housekeeping gene, such as GAPDH or Actin. Theincreased (or otherwise abnormal) expression of Target Genes in cancertissue-relative to normal tissue from the same patient—is preferablyconfirmed. Although GAPDH and Actin are considered housekeeping genes,there are reports that such genes are expressed at higher levels intumor cells and that other genes, such as ribosomal protein genes(RPS27A, RPL19, RPL11, RPS29, or RPS3) or, perhaps, a more robustexpression signature control would be more useful as a comparator.

shRNA & siRNA Design and Synthesis

Current methods in designing shRNA and siRNA (two different methods ofRNAi) often employ a set of computer-implemented rules, which are notalways reliable and essentially represent a trial-and-error approach. Asused herein, “RNAi molecules” refers generally to conventional shRNAmolecules (the well-known shRNA molecules routinely used by those ofordinary skill in the art), enhanced shRNA (the novel shRNA moleculesand uses thereof encompassed by the present invention and describedbelow) and/or siRNA molecules. As used herein, “shRNA/siRNA,”“siRNA/shRNA,” and like terms refer to conventional shRNA, enhancedshRNA, siRNA, or any combination of the foregoing.

Recent studies have indicated rather wide-spread off-target effects ofsiRNAs (and other RNAi molecules). Although a target gene may beeffectively silenced, non-specific effects both at the mRNA and proteinlevels have been reported. Accordingly, for the clinical applications ofthe present invention described herein, it is important to incorporateRNAi molecules with desirable potency, efficacy, and binding precisionand accuracy. In certain embodiments of the invention, the RNAimolecules are preferably conventional or enhanced shRNAs, as suchdesigns have been shown to be more stable, durable, potent and amenableto regulation than siRNAs. In addition, the incorporation oftumor-specific targeting of the delivery vector and tumor-specificpromoters may be utilized, thereby adding a multiple-log safety bufferto the invention.

For each selected Target Gene, the invention provides that a literaturesearch may be conducted to identify any commercially-available shRNA-and siRNA-encoding plasmids that have been shown to modulate theexpression of the Target Gene and/or exhibit other preferredcharacteristics (such as potency, efficacy, and binding precision andaccuracy). Additional information regarding such Target Gene, siRNAs,and/or shRNA may, preferably, be obtained from The Cancer Genome AnatomyProject's RNAi site of NCI (cgap.nci.nih.gov/RNAi). If appropriatecommercially-available shRNA- and/or siRNA-encoding sequences exist,such compositions or components thereof may be used in the presentinvention (assuming such compositions satisfy other preferred criteria,such as those relating potency, efficacy, and binding precision andaccuracy).

If there are no commercially-available siRNAs or shRNA clones for theselected Target Gene, an appropriate number of shRNAs and/or siRNAs maybe designed, such as two, three, four, five, or more shRNAs and/orsiRNAs, using readily-available RNAi molecule design computer programs.Synthetic shRNA/siRNA duplexes of HPLC grade may be purchased from anyof numerous suppliers, such as Qiagen or IDT.

If there are no commercially-available siRNA or shRNA clones for aTarget Gene (and shRNAs and/or siRNAs that are designed using computersoftware do not demonstrate, for example, desirable efficacy), a“shotgun” approach may be employed. For example, shRNA expression clonesynthesis technology, developed by SilereTech, enables the synthesis ofa “shotgun” library of shRNA expressing vectors for a given targetsequence (e.g., Target Gene). The shotgun library provides thousands ofRNAi candidates that are randomly distributed along the target sequence.From the shotgun library, numerous shRNA expressing vectors with variedpotency and efficacy may be identified. The shotgun library provides arich source of representative RNAi molecules (e.g., shRNAs or siRNAs)that do not require repeated synthesis, testing, or vector construction.With a proper screening process, shRNA and/or siRNA expression vectorsof desired potency and efficacy may be readily identified.

The invention provides that the shRNA and/or siRNA sequences purchased,designed, or otherwise identified (using the above-mentioned “shotgun”approach) are, preferably, reviewed for unwanted “off-target” effects(i.e., binding to sequences other than the intended Target Gene). Forexample, the predicted “off-target” effects, or lack thereof, of a shRNAor siRNA molecule may be analyzed by conducting a BLAST search againstirrelevant gene sequences of the NCBI GeneBank database.

In addition to shRNA/siRNA-mediated inhibition of gene expression, theinvention provides that other appropriate methods may be employed tomodulate the expression of one or more Target Genes. While the use ofshRNA/siRNA to modulate gene expression is used throughout the presentspecification, the invention provides that such other appropriatemethods may be used in addition to (or in replacement of) shRNA/siRNAmethods. For example, the invention provides that other transcriptionaland/or translation inhibitors may be employed to modulate Target Geneexpression. Non-limiting examples of transcriptional modulators mayinclude helix-turn-helix, zinc finger, leucine zipper, and/orhelix-loop-helix proteins. Non-limiting examples of translationalinhibitors/modulators may further include other forms of antisensetechnology, as well as siRNA-binding proteins, miRNAs, miRNA-bindingproteins, small molecular inhibitors (e.g., anisomycin, cycloheximide,emetine, harringtonine and puromycin), and like compositions.

Enhanced shRNA Molecules

The invention further provides that a new, improved, and moreefficacious method of using shRNAs to modulate Target Gene expressionmay be employed. In general, shRNAs consist of a stem-loop structurethat may be transcribed in cells from an RNA polymerase III promoterwithin a plasmid construct. Expression of shRNA from a plasmid is knownto be relatively stable, thereby often providing strong advantages overthe use of synthetic siRNAs. shRNA expression units may be incorporatedinto a variety of plasmids and viral vectors for delivery andintegration. shRNAs are synthesized in the nucleus of cells, furtherprocessed and transported to the cytoplasm, and then incorporated intothe RNA-induced silencing complex (RISC) where the shRNAs are convertedinto active siRNA-like molecules (which are capable of binding to andpreventing the translation of mRNA transcripts from Target Genes).

Plant and animal cells have recently been shown to express a novel classof short, single-stranded RNAs termed micro-RNAs (miRNAs). miRNAs arederived from larger precursors that also form a predicted RNA stem-loopstructure. These miRNA precursor molecules are transcribed fromautonomous promoters or are instead contained within longer RNAs. miRNAsappear to play a key role in the regulation of gene expression at thepost-transcriptional level through translation repression. Thebiological activity of two miRNAs, C. elegans let-7 and lin-4, arewell-established.

Similar to mRNAs, miRNAs are initially transcribed by RNA polymerase IIinto a long primary transcript (pri-miRNA), which contains one or morehairpin-like stem-loop shRNA structures. The stem-loop shRNA structureswithin the pri-miRNAs are further processed in the nucleus by the RNaseIII enzyme Drosha into pre-miRNA. Pre-miRNAs are transported to thecytoplasm by the nuclear export factor Exportin-5, where it interactswith a second RNase III enzyme known as Dicer. Dicer trims off the loopand presents the remaining double stranded stem to the RISC to seek-outtarget mRNAs for down-regulation.

RISC may be characterized into cleavage-dependent RISC andcleavage-independent RISC (FIG. 2B). The invention provides thattarget-specific shRNAs may be designed to enter into and interact witheither cleavage-dependent RISC or cleavage-independent RISC.

The enhanced shRNAs employed in the present invention comprise bothtypes of shRNAs, namely, shRNAs designed to enter into and interact withboth cleavage-dependent RISC and cleavage-independent RISC (FIG. 2A).The invention provides that a higher level of gene “knock-down,” i.e.,translation repression of Target Gene mRNA transcripts, is achievedusing such enhanced shRNAs than other currently-available RNAi methodsand compositions.

More specifically, the present invention provides methods andcompositions for the synthesis of novel shRNA molecules that may betranscribed endogenously in human, animal and plant cells, for thepurpose of “knocking down” the expression of one or more Targeted Genes.The shRNAs of the present invention simultaneously enter bothcleavage-dependent RISCs and cleavage-independent RISCs, and inhibit theexpression of a targeted mRNA containing a complementary target sequence(FIGS. 2A and 2B).

The invention provides that nucleic acid sequences, and constructsthereof, are used that encode one or multiple sets of shRNAs, wherein atleast a portion of the shRNAs structurally resemble miRNAs. Theresulting shRNAs induces degradation of a Target Gene mRNA produced inthe cell, wherein the shRNAs contain a complementary target sequence orotherwise inhibits translation of such mRNA.

The constructs encoding the enhanced shRNAs described herein comprise apromoter, which is operably linked to a sequence encoding a precursor ofthe enhanced shRNAs. Preferably, the promoter is preferentially activein the targeted tumor tissues (i.e., it is a tumor tissue-specificpromoter). Introduction of such constructs into host cells may beeffected under conditions whereby the enhanced shRNA precursortranscript is produced, which is subsequently excised from suchprecursor by an endogenous ribonuclease. The resulting mature shRNAs maythen induce degradation of Target Gene mRNA transcripts produced in thecell or otherwise repress translation of such mRNAs.

The enhanced shRNAs encompassed and employed by the present inventionare, preferably, about 19-24 nucleotides long, or more preferably, about21 or 22 nucleotides in length. The enhanced shRNAs may be designed soas to hybridize to any RNA transcript with a high degree of specificity.Preferably, a first portion of the enhanced shRNAs are designed to beperfectly (about 100%) complementary to the target sequence within thetargeted RNA (e.g., mRNA). Still further, a second portion of theenhanced shRNAs are preferably designed to be perfectly (about 100%)complementary to the target RNA at positions 2-10, along withthermodynamically-favorable interspersed mis-matches at the remainingpositions (FIGS. 10A and 10B and 11A to 11E).

Accordingly, a first aspect of the enhanced shRNAs will, preferably,promote the cleavage of mRNAs bearing a fully complementary target site,while a second aspect of the enhanced shRNAs will, preferably, inhibitexpression of mRNAs bearing partially complementary sequences (withoutnecessarily inducing cleavage). The invention provides that simultaneousexpression of both aspects of the enhanced shRNAs in cells establishesconditions within effected cells such that RNA interference may beactivated through cleavage-dependent and cleavage-independent processes.The enhanced shRNAs may be designed so as to target a 3′ or 5′untranslated region of the Target Gene mRNAs or coding regions thereof

As described above, miRNAs are excised from precursor molecules thatinclude a predicted RNA stem-loop structure. This RNA stem-loopstructure of the enhanced shRNAs molecules encompassed and employed bythe present invention may be designed such that it is recognized andproperly processed by a ribonuclease (e.g., an RNAse III-type enzyme,such as Drosha and Dicer, or an enzyme having the recognition propertiesthereof), with the resulting excision of the mature siRNAs and miRNAs.Such precursor stem-loop structures may be about 40 to 100 nucleotideslong or, preferably, about 50 to 75 nucleotides long. The stem regionmay be about 19-45 nucleotides in length (or more), or more preferablyabout 20-30 nucleotides in length. The stem may comprise a perfectlycomplementary duplex (but for any 3′ tail), however, bulges or interiorloops may be present, and even preferred, on either arm of the stem. Thenumber of such bulges and asymmetric interior loops are preferably fewin number (e.g., 1, 2 or 3) and are about 3 nucleotides or less in size.

The stem regions of the enhanced shRNAs comprise passenger-strands andguide-strands, whereby the guide-strands contain sequences complementaryto the target RNA (and provide guidance for target sequence search).Preferably, the G-C content and matching of guide stand and passengerstrand is carefully designed for thermodynamically-favorable strandunwind activity with or without endonuclease cleavage. Furthermore, thespecificity of the guide strand is preferably checked via a BLAST search(www.ncbi.nlm.nih.gov/BLAST). The terminal loop portion may compriseabout 4 or more nucleotides (preferably, not more than 25). Moreparticularly, the loop portion is preferably 6-15 nucleotides in size.The precursor stem loop structure may be produced as part of a larger,carrier transcript (the primary transcript) from which the shRNAs areexcised, or it may be produced as a precise transcript. Splice donor andacceptor sequences may be strategically placed in the primary transcriptsequence to promote splicesome-mediated nuclear processing.

In certain embodiments, the enhanced shRNA-encoding sequence maycomprise stem sequences of naturally occurring miRNAs (such as miR-30)to generate miRNAs suitable for use in inhibiting expression of anyTarget Gene. While the presence of a miR-30 loop may be desirable, theinvention provides that variations of that structure may be tolerated,wherein loops may be used that are greater than 72%, preferably greaterthan 79%, more preferably greater than 86%, and most preferably, greaterthan 93% identical to, for example, the miR-30 sequence (determinedusing well-known computer programs such as the BESTFIT program(Wisconsin Sequence Analysis Package, Version 8 for Unix, GeneticsComputer Group, University Research Park, 575 Science Drive, Madison,Wis. 53711)). The enhanced shRNA designs of the invention preferablymimic miRNAs expressed in the target tissue.

The enhanced shRNA encoding sequences (i.e., the sequences encoding theenhanced shRNAs precursors) may be present in a construct in operablelinkage with a promoter. Appropriate promoters may be selected based onthe host cell and effect sought. Suitable promoters include constitutiveand inducible promoters, such as inducible RNA polymerase II (polII)—based promoters. Examples of suitable promoters include thetetracycline inducible or repressible promoter, RNA polymerase I orIII-based promoters, the pol II dependent viral promoters, such as theCMV-IE promoter, and the pol III U6 and H1 promoters. The bacteriophageT7 promoter may also be used (in which case, it will be appreciated,that the T7 polymerase must also be present).

The constructs encoding the enhanced shRNAs may be introduced into hostcells using any of a variety of techniques and delivery vehicleswell-known in the art. For example, infection with a viral vectorcomprising one or more constructs may be carried out, wherein such viralvectors preferably include replication defective retroviral vectors,adenoviral vectors, adeno-associated vectors, lentiviral vectors, ormeasle vectors. In addition, transfection with a plasmid comprising oneor more constructs may be employed. Such plasmids may be present asnaked DNA, or may be present in association with, for example, aliposome (e.g., an immunoliposome). Still further, the delivery vehiclemay consist of immunolipoplexes, RGD targeted nanoparticles, RGDtargeted liposomes, nanoparticles, aptamers, dendrimers, chitosan, orpegylated derivatives thereof. The nature of the delivery vehicle mayvary depending on the target host cell.

In-vivo delivery of the enhanced shRNA-encoding constructs may becarried out using any one of a variety of techniques, depending on thetarget tissue. Delivery may be, for example, achieved by directinjection, inhalation, intravenous injection or other physical methods(including via micro-projectiles to target visible and accessibleregions of tissue (e.g., with naked DNA)). Administration may further beachieved via syringe needles, trocars, canulas, catheters, etc., asappropriate.

Testing Efficacy of RNAi Molecules In-Vitro on Cancer Cell Lines

The shRNAs or siRNAs (and/or other transcriptional and/or translationalmodulating compositions) that are selected to regulate Target Geneexpression are, preferably, tested in vitro on human cancer tissueculture cell lines (e.g., NCI60). While the present specification makesreference to testing the efficacy of the shRNAs and siRNAs that areselected to modulate Target Gene expression, those of ordinary skill inthe art will appreciate that such testing should also be conducted toassess whether any additional or other transcriptional and/ortranslational modulating compositions that may be used in practicing theinvention exhibit desired efficacy.

For each Target Gene, cell lines exhibiting similar, abnormal expressionlevels for such Target Gene are preferably used(cmap.nci.nih.gov/Profiles/ProfileQuery) (discover.nci.nih.gov). In manycases, the cell lines may be obtained from ATCC. The invention providesthat, in some cases, tumor cell lines derived from autologous cancercells may also be reanalyzed for expression-similar to originalharvested tissue and utilized for subsequent validation of shRNA/siRNAeffect. The effect of such shRNAs/siRNAs is, preferably, analyzed withand without unique delivery vehicles. More specifically, the selectedcell line will be transfected with each shRNA/siRNA duplex at aneffective dose range to determine the most optimum dose for each TargetGene. For example, the Block-It™ lipofectamine-based RNAi transfectionkit may be used for such analysis (Invitrogen, Carlsbad, Calif.). Thetransfection efficiency of each cell line will be optimized using thefluorescent oligonucleotides provided with such kit. Quantitative RT-PCRanalysis may be used to determine Target Gene mRNA levels in theselected cell line transfected with such shRNAs/siRNAs (or a controlnon-silencing shRNA or siRNA duplex).

The effective dose range (e.g., 50 nM to 250 nM) and percentageknock-down of each shRNA/siRNA duplex are preferably determined. Next,the most effective siRNA molecule or shRNA constructs for a given TargetGene may be selected for further study (or use in treating a patient asdescribed herein). In certain preferred embodiments, thecharacterization of each siRNA/shRNA for each Target Gene is recorded ina database for future reference (and for future Target Gene selectiondecisions). An additional aspect of this invention is the contributionof the resulting gene perturbation data towards improving a gene networkdatabase computational system through the acquisition of non-confoundeddata derived from human source material.

Next, the ability of each shRNA/siRNA to suppress target protein andtumor cell growth is measured. To demonstrate cell growth arrest, cellsfrom the selected cell line may be seeded the night before at 50%confluency and then transfected with an effective dose of the designedshRNA/siRNA molecule(s). At 24, 48 and 72 hours post-infection, viablecells may be enumerated by tryptan blue exclusion. Control culture forwhich expression of the Target Gene is not abnormally elevated will betransfected with the same dose of the shRNA/siRNA molecules to determinetumor cell specificity of the RNAi molecule(s) employed. Transfectionefficiency of both cell types is, preferably, monitored usingfluorescent oligonucleotides—in order to correct variation intransfection efficiency.

Total RNA from transfected cells may be harvested and the Target Genecontained therein may be subjected to semi-quantitative qRT-PCRanalysis. The invention provides that preferred shRNA/siRNA targetsexhibit effective curtailment of cell growth only in selected,over-expressed cell lines. If no suppression of tumor cell growth andquantitative reduction of mRNA is observed, the shRNA/siRNA candidateshould be further tested, preferably in connection with a multiplextreatment strategy in combination with other RNAi molecules. The presentinvention provides that single target knock-down may not be entirelyeffective to completely suppress tumor cell growth, as redundant andoverlapping pathways may compensate for the effects of a singleshRNA/siRNA. Accordingly, the invention provides that multiple, such as2, 3, 4, 5, or more, different shRNAs/siRNAs may be designed and used to“knock-down” the expression of a Target Gene—to effectively suppresstumor growth. In still further embodiments, the invention provides thatmultiple, such as 2, 3, 4, 5, or more, different shRNAs and/or siRNAsmay be designed, tested, and used to “knock-down” the expression ofmultiple Target Genes.

After testing such siRNAs/shRNAs on an individual basis, the effect of acombination of siRNAs/shRNAs may be examined. Such multiplex treatmentmay be identical in condition to the singular siRNA/shRNA treatmentdescribed above. Various combinations of siRNAs/shRNAs may be tested asdescribed for the singular siRNA/shRNA with or without the presence ofdelivery vehicle (e.g., nanoparticle or oncolytic virus). Multiplextreatment may be delivered with a single RNAi molecule expression vectorexpressing multiple RNAi molecules, or multiple RNAi molecule expressionvectors expressing multiple RNAi molecules.

In addition to the foregoing, animal models, such as the SCID mouse (andderivatives thereof), may be used as human tumor tissue growth systemsand the administration of RNAi constructs may be used to demonstrate thedelivery, targeting, safety and overall efficacy of the RNAi constructbeing evaluated.

Parallel Processes

In certain embodiments, the invention contemplates that more traditionalmethods of treating, preventing, and monitoring cancer may be employedbefore, during (i.e., concurrent with), or after the methods of thepresent invention.

Following the procedures for detecting, diagnosing, and treating cancerdescribed herein, the invention further provides that certain monitoringsteps may be undertaken to ensure the targeted cancer does not returnand/or to maintain the target cancer cells at manageable and/or safelevels. Preferably, such monitoring steps may be carried out using flowcytometry.

Diagnostic and Therapeutic Kits & Compositions

In certain additional embodiments of the present invention, kits areprovided for carrying out certain methods described herein. Theinvention provides kits that comprise, for example, (i) a password orother authenticating information that provides a physician or otherindividual with access to a central database, instructions, and/orweb-based software that enables him/her to identify a Target Gene and/ordesign an appropriate RNAi molecule (based on microarray, genomic DNA,and/or proteomic information provided to such database and/or web-basedsoftware); (ii) delivery vehicles capable of receiving and incorporatingone or more RNAi molecule expression cassettes (or other sequencesencoding desired transcriptional and/or translational modifiers) fordelivery to a patient; and/or (iii) other surgical instruments anddisposables that may be necessary to carry out the methods describedherein.

The following examples are provided to further illustrate thecompositions and methods of the present invention. These examples areillustrative only and are not intended to limit the scope of theinvention in any way.

EXAMPLES

The following provides a non-limiting example of how the methodsdescribed herein may be used to identify a set of Target Genes in anindividual suffering from cancer based on differential mRNA and proteinexpression patterns (in malignant versus non-malignant tissues).Furthermore, the following demonstrates that RNAi molecules may bedesigned and used to modulate the expression of such Target Genes toachieve a therapeutic effect.

Example Process for Reducing Cancer Cell Growth

Patient Selection

Patient-1 is a 72-year old male with melanoma and a history of multiplerecurrent disease episodes. He initially underwent two surgicalresections without adjuvant therapy. At the time of the thirdrecurrence, on Mar. 9, 2005, an auxiliary node was resected and tissuewas processed at the Mary Crowley Medical Research Center (Dallas,Tex.).

Prior to surgery, an IRB-approved tissue harvest consent was obtained. Anormal lymph node and skin tissue were resected for comparativeanalysis. Histologic review demonstrated 95% cancer cells in theresected node. The specimens were analyzed for differential anddiscriminatory genomic and proteomic expression as described herein. OnJan. 11, 2006, a PET scan identified areas of uptake in the leftsupraclavicular region, the right pericardiophrenic region, aretroperitoneal node, as well as several ill-defined lung nodules thatwere consistent with metastatic disease. These lesions were notresectable and Patient-1 was biopsied (supraclavicular node) on Jan. 26,2006 a second time for genomic and proteomic analysis. Patient-1received concurrent chemoradiotherapy from Feb. 13, 2006 through Mar.17, 2006 with temozolomide and 45 Gy to the left supraclavicular nodalregion. Patient-1 remains alive with stable disease.

RNA Amplification and Microarray Analysis

RNA was extracted from the malignant and non-malignant tissues describedabove using a PicoPure RNA Isolation kit (Arcturus Bioscience,Mountainview, Calif.). The quality of captured RNA was examined using anAgilent 2100 Bioanalyzer with RNA 6000 Pico LabChip (AgilentTechnologies, Palo Alto, Calif.). The remainder of the samples weresplit into two equal portions for parallel RNA amplification and geneprofile analysis. R-squared tests were performed to provide an indicatorfor the reproducibility of the duplicate portions.

RNA was amplified before labeling using a RiboAmp RNA amplification Kit(Arcturus Bioscience, Mountainview, Calif.). The quality of theamplified RNA was examined with BioAnalyzer. Genes exhibiting malignanttissue/non-malignant tissue expression level ratios equal to or morethan >1 were determined to be “over-expressed.” This ratio wasdetermined with tissue-extracted nucleic acids (RNA), whereby themalignant tissue sample and normal tissue sample were analyzed inpair-wise fashion to identify genes that are significantly upregulatedin the malignant tissue.

This “pair-wise” expression level analysis was carried out throughbinding reactions (i.e., GeneChip microarray hybridization reactions)with gene probes that were specific for 38,500 individual human genes.Gene expression profiles were established using bioinformatics analysis(Gene Spring 7.2 software). Specifically, hybridization and processingof GeneChip data were performed using an automated GeneChip InstrumentSystem. Data acquisition, sample normalization and initial data analysiswas performed with Affymetrix Microarray Suite (MAS) software. Geneprobes with significant present cells (p-value<0.05) were selectedfollowing quantile normalization from bioconductor(www.bioconductor.org) to correct for systematic bias among samples.

Proteomics (2D-DIGEIMS) and Data Analysis

10 mg of malignant and non-malignant human lymph node tissue (fromPatient-1) was lysed in 2-D lysis buffer containing 30 mM Tris-HCl (pH8.8), 7 M urea, 2 M thiourea and 4% CHAPS. Cleared non-malignant proteinlysate was labeled with a Cy3 CyDye fluor (green) for 30 minutes at0[deg.] C., while malignant protein lysate was labeled with a Cy5 CyDyefluor (red) under the same conditions.

The reactions were terminated with the addition of lysine, and samplesto be compared were mixed in an equal molar ratio. Destreak solution andrehydration buffer were added (100 [mu]l each) before samples wereloaded onto a 13-cm IPG strip (pH 3-10 linear range, Amersham) forisoelectric focusing (IEF) separation. After IEF was completed, the IPGstrip was incubated with SDS-containing equilibration solutions andapplied to a 9-12% gradient SDS gel (18*16 cm, 1-mm thickness).Electrophoresis was performed. The gel was subsequently scanned using aTyphoon Trio scanner (GE Healthcare/Amersham), and the images wereanalyzed using ImageQuant and DeCyder software. Protein spots ofinterest were excised and identified using MALDI-ToF/ToF massspectrometry.

Gene Expression Profile Analysis and RNAi Selection

High-quality raw data from microarray and 2D-DIGE/MS were analyzed usingthe GNS network analysis system described above to identify potentialRNAi targets (i.e., Target Genes). The list of targets was prioritizedsequentially. First, proteins that were present in malignant tissue atlevels that were at least 2-fold higher than in non-malignant tissuewere identified (referred to herein as “highly-expressed proteins”).Second, the highly-expressed proteins were identified and functionallycharacterized for processes associated with oncogenesis, such asangiogenesis, apoptosis, cell cycle, cell cycle gene, DNA repair,migration, proliferation, signaling, stem cell association, andtranscription activity through known literature searches. Third,highly-expressed proteins found to be implicated in cancer processes andelevated mRNA expression (>1.5 fold) in the tumor tissue were weightedas higher priority. Additionally, highly-expressed proteins known toexhibit high cross-species DNA sequence conservation were identified ashigher priority. Fourth, for each of the proteins (and correspondingTarget Genes) that met these criteria, protein-protein interactionsfulfilling Gene Ontology (GO) assignments, which are frequently assignedto known cancer causing genes (determined through an enrichment analysisof GO terms assigned to oncogenes catalogued in the Cancer Census), wereobtained from the human protein interaction databases of BIND, HPRD, andResNet 33-35. The most highly-connected proteins (and correspondingTarget Genes) were selected for further analysis.

Design & Synthesis of siRNAs

For each selected highly-connected protein (and corresponding TargetGene), the scientific literature was reviewed for the purpose ofidentifying commercially-available siRNA molecules from the CancerGenome Anatomy Project's RNAi site of NCI (cgap.nci.nih.gov/RNAi) andfrom appropriate vendors (www.ambion.com). Commercial siRNA sequences ofHPLC grade were available and purchased (synthetic predesigned proteinspecific siRNA duplexes) for each of the highly-connected proteins (andcorresponding Target Genes).

In-Vitro Efficacy of siRNAs on Cancer Cell Lines

Selected siRNAs were tested on human cancer tissue culture cell linesHCT 116 Colon Cancer Cell Line (CCL247) and MDA-MB-231 AdenocarcinomaBreast (HTB26) from ATCC (Manassas, Va.). For each selected RNAi TargetGene, gene expression data compiled for NCI 60 cell lines were comparedto identify those cell lines that have similar abnormally-highexpression levels of the Targeted Genes(cmap.nci.nih.gov/Profiles/ProfileQuery) (discover.nci.nih.gov). Eachselected cell line was tested for a group of identified Target Genesthat are over-expressed. The cell lines were obtained from ATCC andutilized to validate siRNAs.

The RNAi activity for each siRNA on selected cell lines was determined.Specifically, the cells were transfected with each siRNA duplex across arange of doses to determine the optimum dose for each siRNA moleculeusing the (siPORT™ NeoFX lipid based RNAi transfection kit from Ambion,Austin, Tex.). A control non-silencing siRNA duplex with scrambledsequence was used to determine target mRNA level in selected cell lines.A time course of knock-down was then determined.

The ability of each siRNA molecule to suppress tumor cell growth wasalso measured. Specifically, cell growth arrest of transfected cells atDay-1, Day-2, Day-4, and Day-7 post-infection was tested using thewell-known trypan blue exclusion method. Transfection efficiency wasmonitored with fluorescent oligonucleotides (Ambion, Austin, Tex.) inorder to correct variation in transfection efficiency. RNA and proteinsamples were harvested from transfected cells and subjected tomicroarray and 2D DIGE/MS analysis (as described herein), withcomparison of baseline at 24- and 72-hours post-transfection times.

Immunohistochemical Evaluation

Frozen malignant tissue cryosections and/or Formalin Fixed ParaffinEmbedded sections were tested by immunohistochemically staining thecells expressing the selected proteins (i.e., those encoded by theTarget Genes) using selected primary antibodies from BD Biosciences (SanDiego, Calif.) and Abcam (Cambridge, Mass.). Staining was performedusing the Universal Quick kit from Vector Laboratories Vectastain®(Burlingame, Calif.) and color development was achieved using a DAB(3,3′-diaminobenzenidine) substrate for the peroxidase enzyme antibodylabel (Vector Laboratories). Counter stain was achieved usingHematoxylin. Relevant unlabeled IgG antibodies were used as a negativecontrol.

Western Blot Analysis

Paired tissue sample total protein—from both malignant and non-malignantsamples—was tested by Western blot for the selected Target Gene proteinexpressions. Normal peripheral blood mononuclear cells, skin, andunaffected lymph node tissue were used as control. Total protein fromcell lines expressing the selected Target Gene proteins were extractedand tested by Western blot analysis. Cell lines showing the expressionof the selected Target Gene proteins were transfected using siPORT™NeoFX™ Transfection Agent (Ambion, Austin, Tex.) with Silencer®Pre-designed siRNA for the target gene, transfection reagent alone and aSilencer® Negative Control #1 siRNA of 19 bp scrambled sequence with 3′dT overhangs (Ambion) for time periods of 24 hours, 48 hours, 4 days and7 days. Total cell protein was extracted using CelLytic™ M (Sigma, SaintLouis, Mo.) and supplemented with Protease Inhibitor Cocktail (Sigma).

The protein concentration estimation was performed using Coomassie(Bradford) Protein Assay Kit (Pierce, Rockford, Ill.). The proteins wereseparated based on Molecular Weight using 15% Ready Gels (Bio-Rad,Hercules, Calif.) and SDS PAGE, transferred to High Bond PVDF membrane(Bio-Rad), probed with Target Gene protein-specific primary antibody (BDBiosciences), followed by enzyme labeled (HRP) secondary antibody anddetected using the ECL Plus Western blotting detection reagents. Actinwas also detected in the Western blots to show the loading concentrationof samples. Band densities were estimated using AlphaImager 2000D (AlphaInnotech, San Leandro, Calif.) and NIH/Scion Image Software (Scion,Frederick, Md.).

Proteomics Results

Sixteen proteins were identified with 2-fold differential expression bymass spectrometry. The proteins were identified as: MDH2, syntenin,Stathmin 1, elongation factor Tu mitochondrial precursor, pyruvatekinase 3 isoform 2, hnRNP L protein, hnRNP d-like protein JK TBP 10,hnRNP A2/B1, TPI1, VDAC2, heat shock protein 90, RACK 1,glyceraldehyde-3 phosphate dehydrogenase, immunoglobulin heavy chainbinding protein, phosphoglycerate kinase 1, and adenylylcyclase-associated protein. These potential targets were thenprioritized via the protein network analysis system described above.Five proteins satisfied the selection criteria, which are listed in FIG.9. An example comparison of protein profiles between non-malignant andmalignant tissue is shown in FIGS. 3A and 3B and 4A to 4C. Proteomicanalysis performed on tissue harvested on Jan. 26, 2006, following a10-month period of no detectable disease in the patient, indicatedconservation of all original proteins, including the 5 selected targetproteins (FIGS. 4A to 4C).

Connectivity of Priority Proteins

The priority proteins identified in Patient-1 following massspectrometry of over-expressed 2D DIGE spots and parallel correlationwith mRNA expression were further assessed for degree of connectivity byfirst order protein linkage analysis. The network analysis demonstratedhighest connectivity of three proteins, namely, RACK1, Syntenin, andStathmin 1 (FIGS. 5A to 5C). Based on this analysis, RACK1 was selectedas the highest priority protein target for RNAi validation (i.e., theTarget Gene of highest priority). Remarkable second order linkage (viaintermediary protein interaction) between target proteins RACK1 andStathmin 1 are shown in FIGS. 5A to 5C.

Immunohistochemical Staining Results

Fresh frozen tissue from Patient-1 was harvested on Jan. 26, 2006 andsubjected to immunohistochemical staining using mouse polyclonalantibody (diluted to a final concentration of 5 [mu]g/ml) raised againstRACK1 and detected using DAB substrate (as described above). Theimmunohistochemical staining demonstrated diffuse cellular involvementwith the antibodies raised against RACK1 (FIG. 6), as well as Stathminand Syntenin (data shown).

Western Blot Results

Antibodies raised against RACK1, Syntenin, and Stathmin 1 were used inWestern blot analysis of proteins extracted from cancer cells lines HCT116, CCL-247, MDA-MB-231, HTB-26, MDA-MB-4355 and HTB-129. Differentialexpression of RACK1 in malignant and non-malignant tissue is shown bywestern blot analysis in FIG. 7A.

cDNA Microarray Results

Referring to FIGS. 8A and 8B, microarray analysis demonstrated theconsiderable similarity in the identity of over-expressed genes in themalignant tissue harvested on Mar. 9, 2005 to Jan. 26, 2006. Thiscorrelation is consistent with the protein expression patterns describedearlier. The ratios of mRNA expression in malignant versus non-malignanttissues of the top 5 prioritized Target Genes are shown in FIG. 9.

siRNA Knockdown Cell Lines

siRNA knockdown demonstrated >80% knockdown of all 3 “priority”proteins, namely, RACK1, Syntenin, and Stathmin 1. FIG. 7B illustratesthe siRNA knockdown of RACK1. The nucleic acid sequences used in thesiRNA molecule to knockdown RACK1 expression were (a) sense5′-CCUUUACACGCUAGAUGGUtt (SEQ ID NO:23) and (b) antisense5′-ACCAUCUAGCGUGUAMGGtg (SEQ ID NO:24). A cell kill of >50% wascorrelated to RACK1 siRNA knockdown, as shown in FIG. 7C.

Example 2 Enhanced shRNA Molecules

Materials.

All oligonucleotides used in this Example were purchased from IDTDNA(Coralville, Iowa). The human embryonic kidney cells, HEK 293 cells,used in this Example were obtained from ATCC (Manassas, Va.) and weregrown in DMEM (Gibco BRL, Invitrogen) supplemented with 10% fetal bovineserum (Hyclone®, Logan, Utah) and 2 mM L-Glutamine (Gibco BRL (GrandIsland, N.Y.). The human colonic carcinoma HCT116 cells (ATCC CCL247)were obtained from ATCC (Manassas, Va.) and were grown in McCoy's 5Amedium with 2 mM L Glutamine (Hyclone®, Logan, Utah) supplemented with10% fetal bovine serum (Hyclone®, Logan, Utah).

RNA Isolation.

Total cellular RNA was isolated from CCL 247 colon cancer cell using theRNeazy mini-kit (Qiagen, Valencia, Calif.) by following themanufacturer's recommendations.

cDNA Synthesis.

The gene-specific cDNAs used in this Example were synthesized by RT-PCR.cDNA was first synthesized using total RNA and a gene-specific primer(SEQ ID NO:1) and Superscript III (Invitrogen, Carlsbad, Calif.). cDNAwas then further amplified with gene-specific PCR primers (SEQ ID NO:2and 3), which contained Nhe I and Bgl II sites at the ends thereof inorder to facilitate cloning. The PCR products were subsequently digestedwith NheI and Bgl II, and purified from a 0.8% agarose gel beforeligating into a NheI and Bgl II digested psiTEST plasmid.

Reporter-Gene cDNA Fusion Construct.

The psiTEST plasmid was purchased from Invitrogen (San Diego, Calif.).Double-stranded cDNA was digested with Nhe I and Bgl II and subsequentlyligated with NheI- and Bgl II-digested psiTEST for directional insertionof the cDNA.

shRNA Expression Construct.

For each shRNA construct used in this Example, two sixty-nucleotideoligonucleotides with short overlapping complement sequences werepurchased from IDTDNA (Coralville, Iowa). dsDNAs were synthesized byfill-in reaction with high-fidelity Taq DNA polymerase (Invitrogen,Carlsbad, Calif.), digested with Bam HI and Hind III. The appropriatesized DNA was subsequently isolated from agarose gel before insertioninto Bam HI and Hind III sites of a pSilencer 4.1-CMV neo plasmid(Ambion, Austin, Tex.).

siRNAs.

The siRNAs used in this Example were purchased from Ambion (Austin,Tex.). The siRNAs used for the STMN1 (#16428) gene are represented bySEQ ID NO:4 (sense strand) and SEQ ID NO:5 (antisense strand).

Sequence Confirmation.

All sequence determinations were performed by SeqWright (Houston, Tex.),www.seqwright.com/. The following primers were used: psiTEST Forward(SEQ ID NO:6); psiTEST Reverse (SEQ ID NO:7); pSilencer Forward (SEQ IDNO:8); and pSilencer Reverse (SEQ ID NO:9).

Transfection of Cell Lines with siRNA or shRNA.

Reverse-transfection of cell lines was performed with siPort™ NeoFX™ orsiPort™ Amine (Ambion, Austin, Tex.) via the protocol recommended by themanufacturer. Briefly, one hour before transfection, healthy growingadherent cells were trypsinized and resuspended in normal growth mediumat 1*10<5> cells/ml. siPORT NeoFX was diluted (5 [mu]l/well) into apredetermined volume of Opti-MEM 1 medium (100 [mu]l/well) for each6-well plate used. The plate was incubated for 10 minutes at roomtemperature. The siRNAs were diluted into Opti-MEM 1 medium for a finalconcentration of 10 nM-30 nM as required in 100 [mu]l/well volumes ofOptiMEM1.

The diluted siPORT NeoFX and siRNAs were combined and incubated for 10minutes at room temperature. The transfection complexes were dispensedinto empty 6-well plates (200 [mu]l/well). The cells were gently mixedand provided with 2.3 ml of 1*10<5> cells/ml into each well of the6-well plate. The plate was gently agitated to evenly distribute thecomplexes. Final volume of transfection was 2.5 ml/well. The plate wasincubated at 37[deg.] C. After 8 hours of incubation, the cells werechecked for cytotoxicity. If cytotoxicity was noticed, the media wasreplaced with fresh media after 8 hours. Otherwise, the media wasreplaced with fresh media after 24 hours of incubation. The cells wereassayed, as described herein, following 24 hours, 48 hours and 4 dayspost-transfection for protein knock-down by Western blotting, flowcytometry or RT-PCR. Transfections were also performed withLipofectamine™ 2000 (Invitrogen, Carlsbad, Calif.) using the protocolrecommended by the manufacturer.

Secreted Alkaline Phosphatase Assay.

Secreted alkaline phosphatase was assayed with colorimetric EnzoLyte™pNPP Secreted Alkaline Phosphatase Reporter Gene Assay Kit (AnaSpec, SanJose, Calif.). Cell culture media was first incubated at 65[deg.] C. for30 minutes to inactivate the endogenous non-specific alkalinephosphatase. Assays were performed in 96-well plates, with 50 [mu]l ofmedia per well. Triplicate samples were used for each data point andcompared against a standard concentration curve. The GraphPad Prismprogram was used to extrapolate concentration in units of samples fromthe standard curve.

Western Immunoblotting.

Cells were lysed with lysis buffer CellLytic-M (Sigma, Saint Louis, Mo.)and scraped off the surface of the culture dish. The cells wereincubated at room temperature for 30 minutes on a slow shaker andbriefly centrifuged. A small aliquot was removed for proteinconcentration estimation by Coomassie Bradford Plus Assay (Sigma, SaintLouis, Mo.), with BSA as a standard. The SoftMaxPro software program wasused to calculate the protein concentration values (based on a standardcurve).

Equal amounts of protein (5-20 [mu]g) were separated via a pre-assembledgel (15 percent PAGE) using the Mini-Protein II Cell system (Bio-Rad).Following electrophoresis, the separated proteins wereelectro-transferred onto a PVDF membrane under standard conditions. ThePVDF membranes were first blocked using a buffer containing 5% non-fatdried milk in DPBS-T overnight at 4[deg.] C. After two changes of washbuffer, proteins were tagged using a dilution of rabbit polyclonalprimary antibody to Stathmin (Calbiochem-EMD, Biosciences, Inc. LaJolla, Calif.), followed by a HRP-conjugated secondary antibody (Abcam,Cambridge, Mass.). Chemiluminescent detection was performed using ECLPlus Western Blotting Detection reagents (GE HealthCare) with BioMax MRfilms (Kodak). Membranes were stripped and re-probed with a differentantibody for a house-keeping protein, such as [beta]-Actin (for controlpurposes). The membranes were scanned using an Alphalmager 2000 DigitalImaging System (Alpha Innotech Corporation). Quantitative densitometricanalysis was carried out using the Beta Release 2 of Scion Image (ScionCorporation).

Flow Cytometry Analysis.

siRNA- and shRNA-transfected cells were Trypsin-treated and collected.An aliquot of cells was set apart for staining to evaluate the dead andapoptotic cells. The rest of the cells were fixed and permeabilizedusing the Fix and Perm reagent (BD Biosciences) for 20 minutes at4[deg.] C. in the dark. Following permeabilization, cells were incubatedwith primary antibody in 100 [mu]l of staining buffer for 30 minutes at4[deg.] C. in the dark. Fluorescein-tagged secondary antibody was addedto the cells and incubated for 10 minutes. The cells were subsequentlywashed and stored in staining buffer for acquisition of events usingFACS caliber (BD Biosciences). Data were analyzed using FACS PROsoftware.

Viable Cell Count.

Sample cells were diluted 1:10 with DPBS and added to 50 [mu]l oftryptan blue (Tryptan Blue 0.4%, Gibco BRL). Viable cells were countedusing a hemacytometer.

Sequences and Oligonucleotides.

The nucleic acid sequences used for the STMN1 shRNA constructs andsummarized in Table 1 below.

TABLE 1 Sequence Designation SEQ ID Number 0015 SEQ ID NO: 10 0016 SEQID NO: 11 0017 SEQ ID NO: 12 0018 SEQ ID NO: 13 0019 SEQ ID NO: 14 0020SEQ ID NO: 15 0021 SEQ ID NO: 16 0022 SEQ ID NO: 17 0023 SEQ ID NO: 180024 SEQ ID NO: 19 0054 SEQ ID NO: 20 0055 SEQ ID NO: 21 0056 SEQ ID NO:22

The shRNA constructs described herein comprise two nucleic acidsequences referenced in the above Table 1. Each shRNA construct isreference by a combination of the appropriate Sequence Designationsshown therein. For example, shRNA constructs comprising SequenceDesignations 0017 and 0018 in Table 1 above (i.e., SEQ ID NO:12 and 13)and referred to herein as “17/18” or “Construct 17/18.” FIGS. 10A and10B illustrate the location of certain structural dimensions of theseshRNA constructs, including the location of the sense sequence,anti-sense sequence, and mismatches thereof.

Design of shRNA and Expression Constructs.

Enhanced shRNAs were designed to mimic the framework of human pre-miRNAhsa-miR-30 by substituting the mature miRNA sequence with aSTMN1-specific siRNA sequence at the stem region of the stem-loopstructure. Two nucleotides juxtaposition to the STMN1-specific siRNAsequence were modified for efficient processing of the pre-miRNA tomature miRNA. The loop region was also enlarged to 15 bases forefficient Drosha processing of pri-miRNA to pre-miRNA.

To test for the positional effect of the siRNA sequence, theSTMN1-specific siRNA sequences were placed in both orientations-eitheron the ascending strand or on the descending strand of the stem of thestem-loop structure. The prototype designs were Construct 15/16 andConstruct 17/18, with guiding strand (anti-sense) at the ascendingstrand and the descending strand of the stem-loop structure,respectively. The sequence for Construct 15/16 and Construct 17/18 areshown in FIGS. 10A and 10B. The predicted Construct 15/16 and Construct17/18 stem-loop structures are shown in FIG. 11A and FIG. 11B,respectively.

Additional STMN1-specific shRNAs were designed to introduce mismatchesand bulges either at the sense strand or at the anti-sense strand todetermine the structural-functional requirement and efficacy thereof.Introduction of mismatches at the sense strand was designed to test thehypothesis of this invention to shunt shRNA to additional RISC toprovide more effective and target-specific knock-downs (i.e., repressionof gene expression). The predicted structures for each shRNA, withmismatches, are shown FIGS. 11C (Construct 54/18), 11D (Construct55/18), and 11E (Construct 56/18).

shRNA expression units were synthesized by fill-in reaction witholigonucleotides as described above. The synthetic shRNA expressionunits comprised Bam HI and Hind III sites at the 5′ and 3′ ends,respectively, to facilitate the insertion into the psilencer 4.1-CMV Neoexpression vector (Ambion, Austin, Tex.), as shown in FIG. 12. Theexpression construct sequence was confirmed before used for RNAinterference analysis, as described above.

Reporter-cDNA Transcription Fusion Constructs.

Introduction of siRNA or shRNA into mammalian cells rely on an efficienttransfection and delivery system. The transfection efficiency varieswidely from cell line to cell line. Thus, it is often difficult toobtain an effective and accurate assessment of target gene knock-downsfor each siRNA or shRNA by examining the whole cell extract.Additionally, it is often difficult to assess the Target Gene knock-downfor prolonged periods of time. Therefore, a reporter assay system wasused, which revealed the efficacy of each siRNA and shRNA constructdescribed herein, without any bias introduced by the transfectionefficiency.

The reporter-cDNA transcription fusion system (psiTEST) of Invitrogen(Invitrogen, San Diego, Calif.) was employed. The psiTEST system used asoluble form of alkaline phosphatase (sAP) as the reporter gene. sAPactivity may be easily sampled and assayed from culture media. STMN1cDNAs were synthesized by RT-PCR with gene specific primers, asdescribed above. STMN1 cDNA was inserted into the psiTEST vector downstream from the mRNA sequence for the soluble form of the alkalinephosphatase gene to form a transcriptional fusion construct. Theresulting fusion construct is illustrated in FIG. 13. It was envisagedthat sequence-specific knock-down of STMN1 will result in knock-down ofthe transcripts of reporter gene-fusion expression, thereby leading tocurtailment of sAP expression. Fusion constructs with STMN1 cDNA wassequenced and confirmed for the inserted cDNA sequence, as describedabove.

Reporter-cDNA Transcription Fusion Assay.

The reliability of the reporter-cDNA transcription fusion system wasfirst determined. Specifically, HEK-293 cells were co-transfected withpsiTEST/STMN1 and various shRNA constructs. The shRNA expression vectorto psiTEST/STMN1 expression vector was co-transfected at a 3:1 ratio.For each transfection, triplicate samples were collected at 18 hours and24 hours post-transfection, and assayed for alkaline phosphatase (AP)activity in the medium. AP assay was performed using pNPP, acalorimetric substrate for AP, vis-à-vis OD620 readings. FIG. 14 showsthe results of this experiment.

As shown in FIG. 14, the assay process was very consistent—withtriplicate samples, it showed little variation between the triplicates.The 24-hour samples exhibited a consistent pattern as the 18-hoursamples with much shorter color development time, indicating increasedaccumulation of AP activity in the media. When compared to siTEST/STMN1transfection alone (FIG. 14, sample #2), all shRNA co-transfectioneffectively reduced the sAP activity in the media (FIG. 14, samples#3-10). Mock transfection without any plasmid DNA showed very littlebackground sAP activity contributing from the cell or serum (FIG. 14,sample #1).

shRNA Knock-Down Persists while siRNA Knock-Down Looses its Effect OverTime.

The abilities of the siRNAs and shRNAs to knock-down Target Geneexpression were compared over a course of approximately 5 days. HEK-293cells were reverse-transfected with reporter construct+ non-specificDNA, or reporter construct+shRNA expression Constructs (Constructs17/18, 17/19, 17/20, or 17/21), or reporter construct+siRNA (16428). A3:1 molar ratio of shRNA and siRNA to reporter gene construct wasemployed. At 12 hours post-transfection, aliquots of samples were taken,and the culture media was replaced with fresh media to remove anyresidual siRNA or shRNA. The culture media was sampled at a regularinterval for up to 5 days (media was not changed).

In order to compare sAP activity for each time point, the sAP assay wascompared to a standard curve generated by known units of AP. FIG. 15shows that psiTEST/STMN1-alone transfected cells continued to accumulatesAP activity in the culture media (blue line), whereas all shRNAco-transfected cultures exhibited reduced sAP expression. The 24-hourtime point shows a reduced sAP activity in response to a washing step atthe 12-hour time point.

When psiTEST/STMN1 was co-transfected with either 10 nM or 30 nM of16428 siRNA (16428 being a STMN1-specific siRNA targeted at the samesequence as the shRNA constructs described herein), the sAP activityaccumulates in a similar pattern as psiTEST/STMN1 transfection alone,albeit lower in sAP accumulation (FIG. 15, light blue and yellow lines).Thus, siRNA appears to be either less active or otherwise looses itsactivity over time. By Western blotting, it was determined that 10 nM of16428 is the effective dose to knock-down STMN1 expression (data notshown); 3-fold excess of siRNA at 30 nM concentration appear to achievea similar inhibition pattern as for 10 nM. At the saturationconcentration of siRNA, the reporter expression appears to be inhibitedinitially, but the inhibition did not persist as it did with theenhanced shRNAs.

The fact that shRNAs were able to inhibit sAP expression over a 5-dayperiod indicates that once transfected, shRNAs are able to continuouslyshut-down the expression of its targeted gene. Comparable siRNA iseither not as effective, or looses its activity over time. These datashow the considerable advantage, and prolonged activity, of the enhancedshRNAs described herein over conventional siRNAs. [0221] Construct 17/18phasing was more effective than Construct 15/16. The knock-downefficiency of Construct 17/18 was compared to that of Construct 15/16 byWestern immunobloting with STMN1-specific monoclonal antibodies. CCL247cells were transfected with 1, 2 or 3 [mu]g/ml of either Construct 15/16or 17/18. Total cellular proteins were harvested from transfected cellsat 48 hours post-transfection and equal amounts of protein were loadedonto polyacrylamide gels for Western blot analysis, as described above.FIG. 16 shows that both Construct 15/16 and Construct 17/18 were able toknock-down the expression of the STMN1 protein when compared to proteinisolated from mock transfected cells. Construct 17/18 appeared to bemore effective than Construct 15/16.

Flow cytometry was also used to evaluate the population of transfectedcells at the single-cell level. At 24 hours post-transfection, with 3[mu]g of either Construct 15/16 or Construct 17/18, both transfectedcell populations exhibited effectively-reduced expression of STMN1 (whencompared to media alone) (FIG. 17).

However, when 1 [mu]g was used for either Construct 15/16 or Construct17/18 (and single cell populations were analyzed by flow cytometry at 24hours post-transfection), Construct 15/16 was not as effective asConstruct 17/18 at 1 [mu]g/ml (FIG. 17). Thus, positioning of theguiding strand sequence at either side of the stem provides active shRNAmolecules; however, positioning the guiding strand at the descendingstrand of the stem-loop structure appears to be more effective than atthe ascending strand. This empirical observation that positioning theguiding strand at the descending strand of the stem-loop structureprovides a favorable advantage in effective dose, and indicates thatsuch structure is preferred for shRNA processing and activity.

RNAi-Mediated Cell Death and Apoptosis.

Recently, Lovborg and colleagues utilized Hoechst 33342 as a reagentused for multi-parametric evaluation of apoptosis, wherein theydemonstrated that apoptotic cells have increased permeability to Hoechstafter fixation (Lovborg, et al. Mol. Cancer Ther. 2004; 3(5): 521-6).Propedium iodide (PI) is a nucleic acid-binding dye that is notpermeable to cell membranes, only dead cells with permeable membranes(which become stained in the presence of PI dye). This procedure isroutinely used by researchers to identify dead cells within a populationof cells.

On the other hand, Hoechst 33342 is also a nucleic acid-binging dye thatneeds to be transported into cells through an active transport system,in order to identify the live cell population. Lovborg and colleaguesdemonstrated that apoptotic cells with leaky membranes and condensedchromosomes appear to have higher fluorescent intensity than normalcells after fixation (fixed cells lack active transport for Hoechst33342). PI and Hoechst 33342 provide a simple and quick assay system toevaluate shRNA-transfected cell populations. CCL247 cells weretransfected with various shRNA constructs for STMN1. After 24 hours, theincreased population of cells was observed to have increased Hoechst andPI fluorescence at the single cell level. The increase in fluorescencewas observed for STMN1 shRNA transfected cells, but not for mocktransfected cells (FIG. 18).

Enhanced Knock-Down with Combinatorial shRNA Designs IndicateAdvantageous Formulation for RNAi.

The knock-down efficiency was further examined with Constructs 17/18 and54/18 (17/18 with single mismatch) and in combination. CCL247 cells waseither transfected with 17/18 or 54/18 alone or in combination. At 24and 48 hours post-transfection, STMN1 mRNA knock-down was examined byqRT-PCR method and STMN1 protein expression was examined at theindividual cell level by flow cytometry with STMN1 specific antibody.With a combination of 1 [mu]g of 17/18 and 54/18, the treatment resultedin more effective reduction in STMN1 mRNA than 3 [mu]g of either 17/18or 54/18 alone (FIG. 19). In terms of promoting STMN1-specific mRNAdegradation, the combination of 17/18 and 54/18 is an advantageousformulation.

At the cell population level, the combination of 17/18 and 54/18 appearsto be similarly effective as the 17/18 or 54/18 alone at 24 hourspost-treatment (FIG. 20). In addition, at 48 hours, cell recovery forthe combination of 17/18 and 54/18 appears to be similarly effective asthe 17/18 alone (FIG. 20). 54/18 treatment alone, however, resulted in amore prolonged effect, further persisting to 48 hours. Such data furtherdemonstrate the effectiveness of the enhanced shRNA designs describedherein to effectively reduce target protein expression levels.

The invention provides that using a combinatorial approach, particularlywith the enhanced shRNAs described herein, provides a desirablyefficacious RNAi formulation. Such formulations were shown to providesuperior efficacy in comparison to other currently-availableconventional molecules designed for RNA interference.

Although illustrative embodiments of the present invention have beendescribed herein, it should be understood that the invention is notlimited to those described, and that various other changes ormodifications may be made by one skilled in the art without departingfrom the scope or spirit of the invention.

1. A method for treating cancer, which comprises: (a) obtaining aspecimen of a cancer tissue and a normal tissue from a patient; (b)extracting total protein and RNA from the cancer tissue and the normaltissue; (c) obtaining a protein expression profile of the cancer tissueand the normal tissue; (d) identifying over-expressed proteins in thecancer tissue as compared to the normal tissue; (e) comparing theprotein expression profile to a gene expression profile; (f) identifyingat least one prioritized protein by assessing connectivity of each theover-expressed protein to other cancer-related or stimulatory proteins;(g) designing an RNA interference expression cassette that modulates theexpression of at least one gene encoding the prioritized protein by atleast one of a cleavage-dependent or a cleavage-independent RNAinterference pathway; (h) incorporating the RNA interference expressioncassette into a delivery vehicle; and (i) providing a patient with aneffective amount of the delivery vehicle in an amount sufficient totreat the cancer.
 2. The method of claim 1, wherein the normal tissue isextracted from an area in close proximity to the cancer tissue.
 3. Themethod of claim 1, wherein the cancer and normal tissue is extractedusing laser capture microdissection.
 4. The method of claim 1, whereinthe protein expression profile is obtained using 2D DIGE and massspectrometry, or using one or more microarrays.
 5. The method of claim1, wherein the gene expression profile is a whole genomic analysis usedto obtain an index patient's genetic predisposition to a particularcancer by determining the copy number, structure, location, and sequenceof a particular gene or collection of genes.
 6. The method of claim 5,wherein the whole genomic analysis is defined further as selected fromchromosomal karyotyping, fluorescence in situ hybridization (FISH), genecopy number determination, high resolution genetic footprinting, forprotein-DNA interactions, restriction fragment length polymorphism(RFLP) analysis, single nucleotide polymorphism analysis,high-throughput DNA sequencing, or gene structural features andmutations.
 7. The method of claim 1, wherein proteins are considered tobe over-expressed if the proteins are found in the cancer tissue athigher levels than in the normal tissue.
 8. The method of claim 1,wherein the protein levels must be at least two-fold higher in cancertissue than in normal tissue.
 9. The method of claim 1, wherein the RNAinterference expression cassette encodes one or more enhanced shRNAmolecules or one or more molecules selected from the group consisting ofconventional shRNA molecules and siRNA molecules.
 10. The method ofclaim 1, wherein the delivery vehicle is selected from the groupconsisting of immunoliposomes, immunolipoplexes, RGD targetednanoparticles, RGD targeted liposomes, nanoparticles, aptamers,dendrimers, chitosan, pegylated derivatives thereof, and oncolytic viralvectors.
 11. The method of claim 1, further comprising measuring whetherthe RNA interference expression cassette is capable of suppressing theexpression of one or more genes that encode the at least one or moreprioritized proteins in vitro prior to providing the delivery vehicle toa patient.
 12. The method of claim 11, further comprising measuringwhether the at least one prioritized protein exhibits a reducedexpression level after provision of the delivery vehicle to the patient.13. The method of claim 1, wherein the RNA interference expressioncassette comprises a tumor-specific promoter.
 14. A method for treatingcancer, which comprises: (a) obtaining a specimen of cancer tissue andnormal tissue from a patient; (b) extracting total protein and RNA fromthe cancer tissue and normal tissue; (c) obtaining a protein expressionprofile of the cancer tissue and normal tissue using 2D DIGE and massspectrometry; (d) identifying over-expressed proteins in the cancertissue; (e) obtaining a gene expression profile of the cancer tissue andnormal tissue using one or more microarrays and comparing the resultsthereof to the protein expression profile; (f) identifying prioritizedproteins by assessing connectivity of each the over-expressed protein toother cancer-related or stimulatory proteins; (g) designing an RNAinterference expression cassette to modulate the expression of at leastone or more genes that encode the one or more prioritized proteins,wherein the RNA interference expression cassette encodes one or moreenhanced shRNA molecules; (h) incorporating the cassette into anappropriate delivery vehicle, wherein the delivery vehicle is animmunoliposome; and (i) providing a patient with an effective amount ofthe delivery vehicle.
 15. The method of claim 14, wherein the cancer istreated by inhibiting cancer cell growth or inducing cancer cellapoptosis, comprising: (a) preparing one or more RNA interferenceexpression cassettes, wherein the cassettes encode nucleic acidsequences at least substantially complementary to mRNA transcriptsencoded by the RACK1 gene (SEQ ID NO:25), the Syntenin gene (SEQ IDNO:26), and the Stathmin 1 gene (SEQ ID NO:27); and (b) providing theone or more RNA interference expression cassettes to a cancer cell. 16.The method of claim 15, wherein the one or more RNA interferenceexpression cassettes are enhanced shRNA molecules.
 17. The method ofclaim 15, wherein the one or more RNA interference expression cassettesencode one or more molecules selected from the group consisting ofenhanced shRNA, conventional shRNA molecules, and siRNA molecules. 18.The method of claim 17, wherein the gene expression profile is a wholegenomic analysis used to obtain an index patient's geneticpredisposition to a particular cancer by determining the copy number,structure, location, and sequence of a particular gene or collection ofgenes.
 19. The method of claim 18, wherein the whole genomic analysis isdefined further as selected from chromosomal karyotyping, fluorescencein situ hybridization (FISH), gene copy number determination, highresolution genetic footprinting, for protein-DNA interactions,restriction fragment length polymorphism (RFLP) analysis, singlenucleotide polymorphism analysis, high-throughput DNA sequencing, orgene structural features and mutations.
 20. The method of claim 19,wherein the one or more RNA interference expression cassettes areprovided to cancer cells via a delivery vehicle selected from the groupconsisting of immunoliposomes, immunolipoplexes, RGD targetednanoparticles, RGD targeted liposomes, nanoparticles, aptamers,dendrimers, chitosan, pegylated derivatives thereof, and oncolytic viralvectors.
 21. A method for treating cancer, which comprises: (a)obtaining a specimen of cancer tissue from a patient; (b) obtaining aspecimen of normal tissue in the proximity of the cancer tissue fromsuch patient; (c) extracting total protein and RNA from the cancertissue and normal tissue; (d) obtaining a proteomic profile of thecancer tissue and normal tissue using 2D difference in-gelelectrophoresis/mass spectrometry (2D-DIGE/MS); (e) identifying proteinsthat are over-expressed in such cancer tissue compared to normal tissue;(f) obtaining a normalized genomic profile of the cancer tissue andnormal tissue using microarray technology; (g) comparing the expressionprofile of the cancer tissue to that of the normal tissue; (h)prioritizing proteins (and the genes encoding such proteins) withcoupled over-expression that are either previously identified ascancer-related genes or in one of six functional groups postulated asfoundational to the cancer process; (i) designing an appropriate RNAinterference (RNAi) expression cassette to, directly or indirectly,modulate the expression of the genes encoding the prioritized proteins;(j) incorporating said cassette into an appropriate delivery vehicle;(k) providing the patient with an effective amount of the deliveryvehicle to, directly or indirectly, modify the expression of such genesexhibiting abnormal expression levels; (l) assessing the molecularactivity-based reduction in cellular and potentially plasma levels ofthe targeted gene(s) after exposure to treatment (i.e., the deliveryvehicle); and (m) pursuing subsequent treatment, if necessary, based onthe emergence of new priority genes and over-expressed cancer-relatedproteins.